2021/9/16 nezha_rdrop0.1-fgm1.0_f81.46_p74.55_r89.77

evaluate.py

@@ -148,8 +148,8 @@ def analyze_error(ground_truth_path, output_path):
     plt.savefig(os.path.join("tmp", "cm.jpg"))
 
 if __name__ == '__main__':
-    # ground_truth_path, output_path = sys.argv[1], sys.argv[2]
-    ground_truth_path, output_path = "data/ner-ctx0-5fold-seed42/dev.gt.all.json", "output.json"
+    ground_truth_path, output_path = sys.argv[1], sys.argv[2]
+    # ground_truth_path, output_path = "data/ner-ctx0-5fold-seed42/dev.gt.all.json", "output.json"
     for label, score in get_scores(ground_truth_path, output_path).items():
         print(LABEL_MEANING_MAP.get(label, label))
         print(score)

main.py

@@ -19,8 +19,19 @@ def main():
 
     # WARNING：以下配置需要在提交前指定！！！
     # version = "baseline"
-    version = "rdrop0.1-fgm1.0"
-    model_type = "bert_span"
+    # model_type = "bert_span"
+    # dataset_name = "cail_ner"
+    # n_splits = 5
+    # seed=42
+    # --------------------------
+    # version = "rdrop0.1-fgm1.0"
+    # model_type = "bert_span"
+    # dataset_name = "cail_ner"
+    # n_splits = 5
+    # seed=42
+    # --------------------------
+    version = "nezha_rdrop0.1-fgm1.0"
+    model_type = "nezha_span"
     dataset_name = "cail_ner"
     n_splits = 5
     seed=42

main_local.py

@@ -13,14 +13,25 @@
 def main():
     parser = ArgumentParser()
     parser.add_argument("--local_debug", action="store_true", default=True)
-    parser.add_argument("--test_file", type=str, default=None)
+    # parser.add_argument("--test_file", type=str, default=None)
     run_args = parser.parse_args()
     local_debug = run_args.local_debug
 
     # WARNING：以下配置需要在提交前指定！！！
     # version = "baseline"
-    version = "rdrop0.1-fgm1.0"
-    model_type = "bert_span"
+    # model_type = "bert_span"
+    # dataset_name = "cail_ner"
+    # n_splits = 5
+    # seed=42
+    # --------------------------
+    # version = "rdrop0.1-fgm1.0"
+    # model_type = "bert_span"
+    # dataset_name = "cail_ner"
+    # n_splits = 5
+    # seed=42
+    # --------------------------
+    version = "nezha_rdrop0.1-fgm1.0"
+    model_type = "nezha_span"
     dataset_name = "cail_ner"
     n_splits = 5
     seed=42

scripts/run_span.sh

@@ -195,6 +195,61 @@ done
 # 组织机构
 # {'p': 0.8940397350993378, 'r': 0.9507042253521126, 'f': 0.9215017064846417}
 
+for k in 0 1 2 3 4
+do
+python run_span.py \
+    --version=nezha_rdrop0.1-fgm1.0-fold${k} \
+    --data_dir=./data/ner-ctx0-5fold-seed42/ \
+    --train_file=train.${k}.json \
+    --dev_file=dev.${k}.json \
+    --test_file=dev.${k}.json \
+    --model_type=nezha_span \
+    --model_name_or_path=/home/louishsu/NewDisk/Garage/weights/transformers/nezha-cn-base/ \
+    --do_train \
+    --overwrite_output_dir \
+    --evaluate_during_training \
+    --evaluate_each_epoch \
+    --save_best_checkpoints \
+    --max_span_length=40 \
+    --width_embedding_dim=128 \
+    --train_max_seq_length=512 \
+    --eval_max_seq_length=512 \
+    --do_lower_case \
+    --per_gpu_train_batch_size=8 \
+    --per_gpu_eval_batch_size=16 \
+    --gradient_accumulation_steps=2 \
+    --learning_rate=5e-5 \
+    --other_learning_rate=1e-3 \
+    --num_train_epochs=4.0 \
+    --warmup_proportion=0.1 \
+    --rdrop_alpha=0.1 \
+    --do_fgm --fgm_epsilon=1.0 \
+    --seed=42
+done
+# main_local
+# avg
+# {'p': 0.9433435148625493, 'r': 0.949889351487191, 'f': 0.9466051170874838}
+# 犯罪嫌疑人
+# {'p': 0.9784416384354789, 'r': 0.983134767136005, 'f': 0.9807825885621673}
+# 受害人
+# {'p': 0.946600434647625, 'r': 0.981016731016731, 'f': 0.9635013430241745}
+# 被盗货币
+# {'p': 0.8947368421052632, 'r': 0.9475409836065574, 'f': 0.9203821656050956}
+# 物品价值
+# {'p': 0.9842931937172775, 'r': 0.9894736842105263, 'f': 0.9868766404199475}
+# 盗窃获利
+# {'p': 0.9301397205588823, 'r': 0.9688149688149689, 'f': 0.9490835030549899}
+# 被盗物品
+# {'p': 0.9147816938453446, 'r': 0.9024390243902439, 'f': 0.9085684430512017}
+# 作案工具
+# {'p': 0.8863636363636364, 'r': 0.9551020408163265, 'f': 0.9194499017681729}
+# 时间
+# {'p': 0.955661414437523, 'r': 0.9432188065099457, 'f': 0.9493993447397161}
+# 地点
+# {'p': 0.9213002566295979, 'r': 0.9186806937731021, 'f': 0.9199886104783599}
+# 组织机构
+# {'p': 0.9203860072376358, 'r': 0.9466501240694789, 'f': 0.9333333333333333}
+
 # for k in 0 1 2 3 4
 # do
 # python run_span.py \