getting-started.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"getting-started.ipynb","provenance":[],"authorship_tag":"ABX9TyNGqV7AYy+IPXztk2UoW60h"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"id":"MRL1nt3mG8bk"},"source":["# Loading the libraries\n","import tensorflow as tf\n","from tensorflow.keras import Model\n","from tensorflow.keras import Sequential\n","from tensorflow.keras.layers import InputLayer\n","from tensorflow.keras.layers import Dense\n","\n","import pandas as pd\n","import numpy as np"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"0fklhPZFHrm4","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1586204191049,"user_tz":240,"elapsed":302,"user":{"displayName":"Chitta Ranjan","photoUrl":"","userId":"03244148267376825421"}},"outputId":"ac16a14d-75b5-4263-f801-9da11acdc37a"},"source":["tf.__version__"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'2.2.0-rc2'"]},"metadata":{"tags":[]},"execution_count":5}]},{"cell_type":"code","metadata":{"id":"lK2zCT3wHxvm"},"source":["from google.colab import drive\n","drive.mount('/content/gdrive', force_remount=True)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"yNs358chJZHB","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1586204447075,"user_tz":240,"elapsed":1269,"user":{"displayName":"Chitta Ranjan","photoUrl":"","userId":"03244148267376825421"}},"outputId":"a2da5997-526d-4e09-d543-8f1b6f78e41a"},"source":["!pwd"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/content\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"uZPf5v9XJwv1"},"source":["root_path = 'gdrive/My Drive/understanding-deep-learning/codebase'\n","\n","import os\n","os.chdir(root_path)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"rXByzwtvJ-6F"},"source":["!pwd"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"fAz1jxEtKLZB"},"source":["# Fit a simple deep learning model"]},{"cell_type":"code","metadata":{"id":"IBxt4vmcKHAK"},"source":["df = pd.read_csv('data/sampledata.csv')"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"84QGRhjgKRaI","colab":{"base_uri":"https://localhost:8080/","height":204},"executionInfo":{"status":"ok","timestamp":1586204585915,"user_tz":240,"elapsed":298,"user":{"displayName":"Chitta Ranjan","photoUrl":"","userId":"03244148267376825421"}},"outputId":"a71d5673-1838-4eb1-9602-57d1e7057bc9"},"source":["df.head(5)"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>y</th>\n","      <th>x</th>\n","      <th>x1</th>\n","      <th>x2</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>-9.784048</td>\n","      <td>-8.463052</td>\n","      <td>12.654344</td>\n","      <td>-13.851703</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>14.669124</td>\n","      <td>5.006981</td>\n","      <td>24.721533</td>\n","      <td>27.959961</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>-5.974108</td>\n","      <td>-7.279825</td>\n","      <td>-24.617841</td>\n","      <td>-13.336648</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>12.981076</td>\n","      <td>12.752716</td>\n","      <td>-20.995864</td>\n","      <td>4.929438</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.960446</td>\n","      <td>-1.586964</td>\n","      <td>-17.425014</td>\n","      <td>4.199543</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["           y          x         x1         x2\n","0  -9.784048  -8.463052  12.654344 -13.851703\n","1  14.669124   5.006981  24.721533  27.959961\n","2  -5.974108  -7.279825 -24.617841 -13.336648\n","3  12.981076  12.752716 -20.995864   4.929438\n","4   0.960446  -1.586964 -17.425014   4.199543"]},"metadata":{"tags":[]},"execution_count":13}]},{"cell_type":"code","metadata":{"id":"_48vz2HRKS5K"},"source":["X = df.loc[:, df.columns != 'y'].values\n","y = df['y'].values"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"E22WigIUKb5f","colab":{"base_uri":"https://localhost:8080/","height":221},"executionInfo":{"status":"ok","timestamp":1586205294310,"user_tz":240,"elapsed":402,"user":{"displayName":"Chitta Ranjan","photoUrl":"","userId":"03244148267376825421"}},"outputId":"e1d1c23d-7c42-4d16-945a-5105da8e25b6"},"source":["# Dense layer model\n","\n","model = Sequential()\n","model.add(Dense(2, activation='relu', input_shape=(X.shape[1], )))  # Hidden layer\n","model.add(Dense(1, activation='linear'))  # Output layer\n","model.summary()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Model: \"sequential_4\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","dense_2 (Dense)              (None, 2)                 8         \n","_________________________________________________________________\n","dense_3 (Dense)              (None, 1)                 3         \n","=================================================================\n","Total params: 11\n","Trainable params: 11\n","Non-trainable params: 0\n","_________________________________________________________________\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"B67oRN6kK8VT"},"source":["model.compile(optimizer='adam',\n","              loss='mse',\n","              metrics='mse')"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"KsGk8inKL7_i","colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"status":"ok","timestamp":1586205336127,"user_tz":240,"elapsed":22685,"user":{"displayName":"Chitta Ranjan","photoUrl":"","userId":"03244148267376825421"}},"outputId":"4d5750ee-0613-4586-d457-1ea59d857ad6"},"source":["history = model.fit(x=X,\n","                    y=y,\n","                    batch_size=16,\n","                    epochs=500,\n","                    validation_split=0.2).history"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Epoch 1/500\n","5/5 [==============================] - 0s 7ms/step - loss: 33.9786 - mse: 33.9786 - val_loss: 40.0159 - val_mse: 28.0952\n","Epoch 2/500\n","5/5 [==============================] - 0s 8ms/step - loss: 33.8526 - mse: 33.8526 - val_loss: 39.8474 - val_mse: 27.9264\n","Epoch 3/500\n","5/5 [==============================] - 0s 8ms/step - loss: 33.7393 - mse: 33.7393 - val_loss: 39.6982 - val_mse: 27.8048\n","Epoch 4/500\n","5/5 [==============================] - 0s 8ms/step - loss: 33.6472 - mse: 33.6472 - val_loss: 39.5329 - val_mse: 27.6389\n","Epoch 5/500\n","5/5 [==============================] - 0s 8ms/step - loss: 33.5609 - mse: 33.5609 - val_loss: 39.3608 - val_mse: 27.4666\n","Epoch 6/500\n","5/5 [==============================] - 0s 8ms/step - loss: 33.4381 - mse: 33.4381 - val_loss: 39.2048 - val_mse: 27.3297\n","Epoch 7/500\n","5/5 [==============================] - 0s 7ms/step - loss: 33.3315 - mse: 33.3315 - val_loss: 39.0453 - val_mse: 27.1937\n","Epoch 8/500\n","5/5 [==============================] - 0s 7ms/step - loss: 33.2187 - mse: 33.2187 - val_loss: 38.8984 - val_mse: 27.0565\n","Epoch 9/500\n","5/5 [==============================] - 0s 9ms/step - loss: 33.0999 - mse: 33.0999 - val_loss: 38.7456 - val_mse: 26.8980\n","Epoch 10/500\n","5/5 [==============================] - 0s 7ms/step - loss: 33.0104 - mse: 33.0104 - val_loss: 38.6121 - val_mse: 26.7612\n","Epoch 11/500\n","5/5 [==============================] - 0s 8ms/step - loss: 32.8989 - mse: 32.8989 - val_loss: 38.4778 - val_mse: 26.6332\n","Epoch 12/500\n","5/5 [==============================] - 0s 7ms/step - loss: 32.8061 - mse: 32.8061 - val_loss: 38.3371 - val_mse: 26.5037\n","Epoch 13/500\n","5/5 [==============================] - 0s 7ms/step - loss: 32.7296 - mse: 32.7296 - val_loss: 38.1909 - val_mse: 26.3586\n","Epoch 14/500\n","5/5 [==============================] - 0s 8ms/step - loss: 32.6155 - mse: 32.6155 - val_loss: 38.0757 - val_mse: 26.2415\n","Epoch 15/500\n","5/5 [==============================] - 0s 7ms/step - loss: 32.5402 - mse: 32.5402 - val_loss: 37.9372 - val_mse: 26.1028\n","Epoch 16/500\n","5/5 [==============================] - 0s 7ms/step - loss: 32.4433 - mse: 32.4433 - val_loss: 37.8167 - val_mse: 25.9898\n","Epoch 17/500\n","5/5 [==============================] - 0s 8ms/step - loss: 32.3570 - mse: 32.3570 - val_loss: 37.7035 - val_mse: 25.8819\n","Epoch 18/500\n","5/5 [==============================] - 0s 8ms/step - loss: 32.2884 - mse: 32.2884 - val_loss: 37.5857 - val_mse: 25.7682\n","Epoch 19/500\n","5/5 [==============================] - 0s 11ms/step - loss: 32.1775 - mse: 32.1775 - val_loss: 37.4756 - val_mse: 25.6606\n","Epoch 20/500\n","5/5 [==============================] - 0s 8ms/step - loss: 32.1156 - mse: 32.1156 - val_loss: 37.3566 - val_mse: 25.5341\n","Epoch 21/500\n","5/5 [==============================] - 0s 8ms/step - loss: 32.0236 - mse: 32.0236 - val_loss: 37.2561 - val_mse: 25.4551\n","Epoch 22/500\n","5/5 [==============================] - 0s 7ms/step - loss: 31.9522 - mse: 31.9522 - val_loss: 37.1451 - val_mse: 25.3354\n","Epoch 23/500\n","5/5 [==============================] - 0s 7ms/step - loss: 31.8582 - mse: 31.8582 - val_loss: 37.0423 - val_mse: 25.2475\n","Epoch 24/500\n","5/5 [==============================] - 0s 7ms/step - loss: 31.7877 - mse: 31.7877 - val_loss: 36.9363 - val_mse: 25.1549\n","Epoch 25/500\n","5/5 [==============================] - 0s 7ms/step - loss: 31.7133 - mse: 31.7133 - val_loss: 36.8385 - val_mse: 25.0603\n","Epoch 26/500\n","5/5 [==============================] - 0s 7ms/step - loss: 31.6676 - mse: 31.6676 - val_loss: 36.7199 - val_mse: 24.9581\n","Epoch 27/500\n","5/5 [==============================] - 0s 8ms/step - loss: 31.5509 - mse: 31.5509 - val_loss: 36.6353 - val_mse: 24.8647\n","Epoch 28/500\n","5/5 [==============================] - 0s 8ms/step - loss: 31.4733 - mse: 31.4733 - val_loss: 36.5521 - val_mse: 24.7625\n","Epoch 29/500\n","5/5 [==============================] - 0s 9ms/step - loss: 31.4053 - mse: 31.4053 - val_loss: 36.4534 - val_mse: 24.6494\n","Epoch 30/500\n","5/5 [==============================] - 0s 7ms/step - loss: 31.3377 - mse: 31.3377 - val_loss: 36.3471 - val_mse: 24.5382\n","Epoch 31/500\n","5/5 [==============================] - 0s 7ms/step - loss: 31.2315 - mse: 31.2315 - val_loss: 36.2404 - val_mse: 24.4333\n","Epoch 32/500\n","5/5 [==============================] - 0s 7ms/step - loss: 31.1492 - mse: 31.1492 - val_loss: 36.1441 - val_mse: 24.3472\n","Epoch 33/500\n","5/5 [==============================] - 0s 8ms/step - loss: 31.0513 - mse: 31.0513 - val_loss: 36.0633 - val_mse: 24.2658\n","Epoch 34/500\n","5/5 [==============================] - 0s 8ms/step - loss: 30.9640 - mse: 30.9640 - val_loss: 35.9686 - val_mse: 24.1718\n","Epoch 35/500\n","5/5 [==============================] - 0s 8ms/step - loss: 30.8768 - mse: 30.8768 - val_loss: 35.8820 - val_mse: 24.0828\n","Epoch 36/500\n","5/5 [==============================] - 0s 8ms/step - loss: 30.7997 - mse: 30.7997 - val_loss: 35.7791 - val_mse: 23.9761\n","Epoch 37/500\n","5/5 [==============================] - 0s 7ms/step - loss: 30.7264 - mse: 30.7264 - val_loss: 35.6912 - val_mse: 23.8762\n","Epoch 38/500\n","5/5 [==============================] - 0s 8ms/step - loss: 30.6268 - mse: 30.6268 - val_loss: 35.6116 - val_mse: 23.8118\n","Epoch 39/500\n","5/5 [==============================] - 0s 7ms/step - loss: 30.5612 - mse: 30.5612 - val_loss: 35.4990 - val_mse: 23.7010\n","Epoch 40/500\n","5/5 [==============================] - 0s 8ms/step - loss: 30.4459 - mse: 30.4459 - val_loss: 35.4087 - val_mse: 23.6150\n","Epoch 41/500\n","5/5 [==============================] - 0s 8ms/step - loss: 30.3714 - mse: 30.3714 - val_loss: 35.3175 - val_mse: 23.5221\n","Epoch 42/500\n","5/5 [==============================] - 0s 9ms/step - loss: 30.2745 - mse: 30.2745 - val_loss: 35.2328 - val_mse: 23.4271\n","Epoch 43/500\n","5/5 [==============================] - 0s 7ms/step - loss: 30.2024 - mse: 30.2024 - val_loss: 35.1476 - val_mse: 23.3470\n","Epoch 44/500\n","5/5 [==============================] - 0s 8ms/step - loss: 30.1102 - mse: 30.1102 - val_loss: 35.0528 - val_mse: 23.2429\n","Epoch 45/500\n","5/5 [==============================] - 0s 7ms/step - loss: 30.0289 - mse: 30.0289 - val_loss: 34.9665 - val_mse: 23.1440\n","Epoch 46/500\n","5/5 [==============================] - 0s 7ms/step - loss: 29.9215 - mse: 29.9215 - val_loss: 34.8698 - val_mse: 23.0288\n","Epoch 47/500\n","5/5 [==============================] - 0s 8ms/step - loss: 29.8187 - mse: 29.8187 - val_loss: 34.7929 - val_mse: 22.9558\n","Epoch 48/500\n","5/5 [==============================] - 0s 9ms/step - loss: 29.7148 - mse: 29.7148 - val_loss: 34.6978 - val_mse: 22.8648\n","Epoch 49/500\n","5/5 [==============================] - 0s 8ms/step - loss: 29.5849 - mse: 29.5849 - val_loss: 34.6331 - val_mse: 22.7929\n","Epoch 50/500\n","5/5 [==============================] - 0s 7ms/step - loss: 29.5156 - mse: 29.5156 - val_loss: 34.5401 - val_mse: 22.7038\n","Epoch 51/500\n","5/5 [==============================] - 0s 8ms/step - loss: 29.4012 - mse: 29.4012 - val_loss: 34.4415 - val_mse: 22.5932\n","Epoch 52/500\n","5/5 [==============================] - 0s 7ms/step - loss: 29.3020 - mse: 29.3020 - val_loss: 34.3351 - val_mse: 22.4714\n","Epoch 53/500\n","5/5 [==============================] - 0s 8ms/step - loss: 29.1568 - mse: 29.1568 - val_loss: 34.2619 - val_mse: 22.3899\n","Epoch 54/500\n","5/5 [==============================] - 0s 8ms/step - loss: 29.0714 - mse: 29.0714 - val_loss: 34.1686 - val_mse: 22.2848\n","Epoch 55/500\n","5/5 [==============================] - 0s 8ms/step - loss: 28.9445 - mse: 28.9445 - val_loss: 34.0894 - val_mse: 22.2062\n","Epoch 56/500\n","5/5 [==============================] - 0s 7ms/step - loss: 28.8507 - mse: 28.8507 - val_loss: 34.0042 - val_mse: 22.1093\n","Epoch 57/500\n","5/5 [==============================] - 0s 11ms/step - loss: 28.7365 - mse: 28.7365 - val_loss: 33.9153 - val_mse: 22.0191\n","Epoch 58/500\n","5/5 [==============================] - 0s 9ms/step - loss: 28.6532 - mse: 28.6532 - val_loss: 33.8294 - val_mse: 21.9361\n","Epoch 59/500\n","5/5 [==============================] - 0s 7ms/step - loss: 28.5379 - mse: 28.5379 - val_loss: 33.7433 - val_mse: 21.8485\n","Epoch 60/500\n","5/5 [==============================] - 0s 8ms/step - loss: 28.4293 - mse: 28.4293 - val_loss: 33.6648 - val_mse: 21.7657\n","Epoch 61/500\n","5/5 [==============================] - 0s 7ms/step - loss: 28.3102 - mse: 28.3102 - val_loss: 33.5831 - val_mse: 21.6697\n","Epoch 62/500\n","5/5 [==============================] - 0s 7ms/step - loss: 28.2234 - mse: 28.2234 - val_loss: 33.4901 - val_mse: 21.5746\n","Epoch 63/500\n","5/5 [==============================] - 0s 7ms/step - loss: 28.1099 - mse: 28.1099 - val_loss: 33.4121 - val_mse: 21.4828\n","Epoch 64/500\n","5/5 [==============================] - 0s 8ms/step - loss: 28.0187 - mse: 28.0187 - val_loss: 33.3245 - val_mse: 21.3905\n","Epoch 65/500\n","5/5 [==============================] - 0s 7ms/step - loss: 27.8912 - mse: 27.8912 - val_loss: 33.2523 - val_mse: 21.3193\n","Epoch 66/500\n","5/5 [==============================] - 0s 7ms/step - loss: 27.8018 - mse: 27.8018 - val_loss: 33.1875 - val_mse: 21.2484\n","Epoch 67/500\n","5/5 [==============================] - 0s 8ms/step - loss: 27.6910 - mse: 27.6910 - val_loss: 33.1126 - val_mse: 21.1660\n","Epoch 68/500\n","5/5 [==============================] - 0s 7ms/step - loss: 27.6166 - mse: 27.6166 - val_loss: 33.0238 - val_mse: 21.0726\n","Epoch 69/500\n","5/5 [==============================] - 0s 8ms/step - loss: 27.5194 - mse: 27.5194 - val_loss: 32.9360 - val_mse: 20.9699\n","Epoch 70/500\n","5/5 [==============================] - 0s 7ms/step - loss: 27.3800 - mse: 27.3800 - val_loss: 32.8621 - val_mse: 20.8922\n","Epoch 71/500\n","5/5 [==============================] - 0s 7ms/step - loss: 27.2501 - mse: 27.2501 - val_loss: 32.7813 - val_mse: 20.8058\n","Epoch 72/500\n","5/5 [==============================] - 0s 8ms/step - loss: 27.1470 - mse: 27.1470 - val_loss: 32.7039 - val_mse: 20.7170\n","Epoch 73/500\n","5/5 [==============================] - 0s 7ms/step - loss: 27.0303 - mse: 27.0303 - val_loss: 32.6178 - val_mse: 20.6154\n","Epoch 74/500\n","5/5 [==============================] - 0s 8ms/step - loss: 26.9132 - mse: 26.9132 - val_loss: 32.5371 - val_mse: 20.5317\n","Epoch 75/500\n","5/5 [==============================] - 0s 7ms/step - loss: 26.7904 - mse: 26.7904 - val_loss: 32.4486 - val_mse: 20.4355\n","Epoch 76/500\n","5/5 [==============================] - 0s 7ms/step - loss: 26.6655 - mse: 26.6655 - val_loss: 32.3873 - val_mse: 20.3610\n","Epoch 77/500\n","5/5 [==============================] - 0s 10ms/step - loss: 26.5525 - mse: 26.5525 - val_loss: 32.3005 - val_mse: 20.2739\n","Epoch 78/500\n","5/5 [==============================] - 0s 8ms/step - loss: 26.4227 - mse: 26.4227 - val_loss: 32.2283 - val_mse: 20.1943\n","Epoch 79/500\n","5/5 [==============================] - 0s 7ms/step - loss: 26.3060 - mse: 26.3060 - val_loss: 32.1655 - val_mse: 20.1253\n","Epoch 80/500\n","5/5 [==============================] - 0s 10ms/step - loss: 26.1934 - mse: 26.1934 - val_loss: 32.1006 - val_mse: 20.0561\n","Epoch 81/500\n","5/5 [==============================] - 0s 7ms/step - loss: 26.0811 - mse: 26.0811 - val_loss: 32.0174 - val_mse: 19.9620\n","Epoch 82/500\n","5/5 [==============================] - 0s 8ms/step - loss: 25.9792 - mse: 25.9792 - val_loss: 31.9331 - val_mse: 19.8706\n","Epoch 83/500\n","5/5 [==============================] - 0s 8ms/step - loss: 25.8410 - mse: 25.8410 - val_loss: 31.7113 - val_mse: 19.7335\n","Epoch 84/500\n","5/5 [==============================] - 0s 7ms/step - loss: 25.7460 - mse: 25.7460 - val_loss: 31.4133 - val_mse: 19.5825\n","Epoch 85/500\n","5/5 [==============================] - 0s 8ms/step - loss: 25.6326 - mse: 25.6326 - val_loss: 31.1037 - val_mse: 19.4139\n","Epoch 86/500\n","5/5 [==============================] - 0s 9ms/step - loss: 25.5047 - mse: 25.5047 - val_loss: 30.7988 - val_mse: 19.2422\n","Epoch 87/500\n","5/5 [==============================] - 0s 8ms/step - loss: 25.3980 - mse: 25.3980 - val_loss: 30.5381 - val_mse: 19.1074\n","Epoch 88/500\n","5/5 [==============================] - 0s 7ms/step - loss: 25.2938 - mse: 25.2938 - val_loss: 30.2166 - val_mse: 18.9163\n","Epoch 89/500\n","5/5 [==============================] - 0s 7ms/step - loss: 25.1733 - mse: 25.1733 - val_loss: 29.8879 - val_mse: 18.7295\n","Epoch 90/500\n","5/5 [==============================] - 0s 7ms/step - loss: 25.0586 - mse: 25.0586 - val_loss: 29.5216 - val_mse: 18.4949\n","Epoch 91/500\n","5/5 [==============================] - 0s 8ms/step - loss: 24.8429 - mse: 24.8429 - val_loss: 29.2196 - val_mse: 18.3215\n","Epoch 92/500\n","5/5 [==============================] - 0s 7ms/step - loss: 24.6964 - mse: 24.6964 - val_loss: 28.9059 - val_mse: 18.1337\n","Epoch 93/500\n","5/5 [==============================] - 0s 8ms/step - loss: 24.5142 - mse: 24.5142 - val_loss: 28.6289 - val_mse: 17.9753\n","Epoch 94/500\n","5/5 [==============================] - 0s 7ms/step - loss: 24.3760 - mse: 24.3760 - val_loss: 28.3128 - val_mse: 17.7854\n","Epoch 95/500\n","5/5 [==============================] - 0s 7ms/step - loss: 24.2021 - mse: 24.2021 - val_loss: 28.0026 - val_mse: 17.6138\n","Epoch 96/500\n","5/5 [==============================] - 0s 9ms/step - loss: 24.0660 - mse: 24.0660 - val_loss: 27.6734 - val_mse: 17.4244\n","Epoch 97/500\n","5/5 [==============================] - 0s 8ms/step - loss: 23.8705 - mse: 23.8705 - val_loss: 27.3853 - val_mse: 17.2597\n","Epoch 98/500\n","5/5 [==============================] - 0s 8ms/step - loss: 23.7222 - mse: 23.7222 - val_loss: 27.0949 - val_mse: 17.1004\n","Epoch 99/500\n","5/5 [==============================] - 0s 7ms/step - loss: 23.5852 - mse: 23.5852 - val_loss: 26.8072 - val_mse: 16.9451\n","Epoch 100/500\n","5/5 [==============================] - 0s 7ms/step - loss: 23.4465 - mse: 23.4465 - val_loss: 26.4870 - val_mse: 16.7650\n","Epoch 101/500\n","5/5 [==============================] - 0s 8ms/step - loss: 23.2914 - mse: 23.2914 - val_loss: 26.2204 - val_mse: 16.6181\n","Epoch 102/500\n","5/5 [==============================] - 0s 7ms/step - loss: 23.1415 - mse: 23.1415 - val_loss: 25.9259 - val_mse: 16.4526\n","Epoch 103/500\n","5/5 [==============================] - 0s 9ms/step - loss: 22.9843 - mse: 22.9843 - val_loss: 25.6252 - val_mse: 16.2918\n","Epoch 104/500\n","5/5 [==============================] - 0s 8ms/step - loss: 22.8562 - mse: 22.8562 - val_loss: 25.3038 - val_mse: 16.1248\n","Epoch 105/500\n","5/5 [==============================] - 0s 9ms/step - loss: 22.6934 - mse: 22.6934 - val_loss: 24.9881 - val_mse: 15.9575\n","Epoch 106/500\n","5/5 [==============================] - 0s 7ms/step - loss: 22.5532 - mse: 22.5532 - val_loss: 24.6814 - val_mse: 15.7918\n","Epoch 107/500\n","5/5 [==============================] - 0s 7ms/step - loss: 22.3791 - mse: 22.3791 - val_loss: 24.3928 - val_mse: 15.6399\n","Epoch 108/500\n","5/5 [==============================] - 0s 8ms/step - loss: 22.2607 - mse: 22.2607 - val_loss: 24.0594 - val_mse: 15.4612\n","Epoch 109/500\n","5/5 [==============================] - 0s 8ms/step - loss: 22.1262 - mse: 22.1262 - val_loss: 23.7563 - val_mse: 15.3033\n","Epoch 110/500\n","5/5 [==============================] - 0s 8ms/step - loss: 21.9388 - mse: 21.9388 - val_loss: 23.4263 - val_mse: 15.1304\n","Epoch 111/500\n","5/5 [==============================] - 0s 8ms/step - loss: 21.7531 - mse: 21.7531 - val_loss: 23.1214 - val_mse: 14.9719\n","Epoch 112/500\n","5/5 [==============================] - 0s 8ms/step - loss: 21.5935 - mse: 21.5935 - val_loss: 22.7780 - val_mse: 14.7907\n","Epoch 113/500\n","5/5 [==============================] - 0s 9ms/step - loss: 21.4166 - mse: 21.4166 - val_loss: 22.4158 - val_mse: 14.6039\n","Epoch 114/500\n","5/5 [==============================] - 0s 8ms/step - loss: 21.2160 - mse: 21.2160 - val_loss: 22.1049 - val_mse: 14.4458\n","Epoch 115/500\n","5/5 [==============================] - 0s 10ms/step - loss: 21.0660 - mse: 21.0660 - val_loss: 21.7399 - val_mse: 14.2486\n","Epoch 116/500\n","5/5 [==============================] - 0s 8ms/step - loss: 20.8592 - mse: 20.8592 - val_loss: 21.4126 - val_mse: 14.0830\n","Epoch 117/500\n","5/5 [==============================] - 0s 7ms/step - loss: 20.6892 - mse: 20.6892 - val_loss: 21.1154 - val_mse: 13.9364\n","Epoch 118/500\n","5/5 [==============================] - 0s 7ms/step - loss: 20.5146 - mse: 20.5146 - val_loss: 20.8024 - val_mse: 13.7789\n","Epoch 119/500\n","5/5 [==============================] - 0s 8ms/step - loss: 20.3635 - mse: 20.3635 - val_loss: 20.4838 - val_mse: 13.6192\n","Epoch 120/500\n","5/5 [==============================] - 0s 8ms/step - loss: 20.2280 - mse: 20.2280 - val_loss: 20.1081 - val_mse: 13.4001\n","Epoch 121/500\n","5/5 [==============================] - 0s 7ms/step - loss: 20.0381 - mse: 20.0381 - val_loss: 19.7908 - val_mse: 13.2119\n","Epoch 122/500\n","5/5 [==============================] - 0s 8ms/step - loss: 19.8959 - mse: 19.8959 - val_loss: 19.4373 - val_mse: 13.0024\n","Epoch 123/500\n","5/5 [==============================] - 0s 8ms/step - loss: 19.7081 - mse: 19.7081 - val_loss: 19.1096 - val_mse: 12.8079\n","Epoch 124/500\n","5/5 [==============================] - 0s 7ms/step - loss: 19.5507 - mse: 19.5507 - val_loss: 18.7879 - val_mse: 12.6246\n","Epoch 125/500\n","5/5 [==============================] - 0s 10ms/step - loss: 19.3809 - mse: 19.3809 - val_loss: 18.4823 - val_mse: 12.4508\n","Epoch 126/500\n","5/5 [==============================] - 0s 9ms/step - loss: 19.2051 - mse: 19.2051 - val_loss: 18.1851 - val_mse: 12.2827\n","Epoch 127/500\n","5/5 [==============================] - 0s 9ms/step - loss: 19.0611 - mse: 19.0611 - val_loss: 17.8960 - val_mse: 12.1215\n","Epoch 128/500\n","5/5 [==============================] - 0s 8ms/step - loss: 18.9152 - mse: 18.9152 - val_loss: 17.5923 - val_mse: 11.9427\n","Epoch 129/500\n","5/5 [==============================] - 0s 8ms/step - loss: 18.7562 - mse: 18.7562 - val_loss: 17.2831 - val_mse: 11.7699\n","Epoch 130/500\n","5/5 [==============================] - 0s 8ms/step - loss: 18.6044 - mse: 18.6044 - val_loss: 16.9855 - val_mse: 11.6014\n","Epoch 131/500\n","5/5 [==============================] - 0s 9ms/step - loss: 18.4641 - mse: 18.4641 - val_loss: 16.6834 - val_mse: 11.4279\n","Epoch 132/500\n","5/5 [==============================] - 0s 8ms/step - loss: 18.2995 - mse: 18.2995 - val_loss: 16.4042 - val_mse: 11.2734\n","Epoch 133/500\n","5/5 [==============================] - 0s 8ms/step - loss: 18.1457 - mse: 18.1457 - val_loss: 16.1328 - val_mse: 11.1198\n","Epoch 134/500\n","5/5 [==============================] - 0s 10ms/step - loss: 18.0125 - mse: 18.0125 - val_loss: 15.8753 - val_mse: 10.9802\n","Epoch 135/500\n","5/5 [==============================] - 0s 7ms/step - loss: 17.8635 - mse: 17.8635 - val_loss: 15.6227 - val_mse: 10.8271\n","Epoch 136/500\n","5/5 [==============================] - 0s 8ms/step - loss: 17.7441 - mse: 17.7441 - val_loss: 15.3554 - val_mse: 10.6712\n","Epoch 137/500\n","5/5 [==============================] - 0s 8ms/step - loss: 17.6310 - mse: 17.6310 - val_loss: 15.0856 - val_mse: 10.5121\n","Epoch 138/500\n","5/5 [==============================] - 0s 8ms/step - loss: 17.4968 - mse: 17.4968 - val_loss: 14.8366 - val_mse: 10.3736\n","Epoch 139/500\n","5/5 [==============================] - 0s 7ms/step - loss: 17.3284 - mse: 17.3284 - val_loss: 14.6080 - val_mse: 10.2407\n","Epoch 140/500\n","5/5 [==============================] - 0s 8ms/step - loss: 17.2180 - mse: 17.2180 - val_loss: 14.3446 - val_mse: 10.0965\n","Epoch 141/500\n","5/5 [==============================] - 0s 9ms/step - loss: 17.0540 - mse: 17.0540 - val_loss: 14.0940 - val_mse: 9.9612\n","Epoch 142/500\n","5/5 [==============================] - 0s 7ms/step - loss: 16.9085 - mse: 16.9085 - val_loss: 13.8378 - val_mse: 9.8228\n","Epoch 143/500\n","5/5 [==============================] - 0s 8ms/step - loss: 16.7636 - mse: 16.7636 - val_loss: 13.5566 - val_mse: 9.6671\n","Epoch 144/500\n","5/5 [==============================] - 0s 9ms/step - loss: 16.5631 - mse: 16.5631 - val_loss: 13.3093 - val_mse: 9.5366\n","Epoch 145/500\n","5/5 [==============================] - 0s 7ms/step - loss: 16.4198 - mse: 16.4198 - val_loss: 13.0470 - val_mse: 9.3893\n","Epoch 146/500\n","5/5 [==============================] - 0s 8ms/step - loss: 16.2846 - mse: 16.2846 - val_loss: 12.7800 - val_mse: 9.2392\n","Epoch 147/500\n","5/5 [==============================] - 0s 8ms/step - loss: 16.0899 - mse: 16.0899 - val_loss: 12.5439 - val_mse: 9.1164\n","Epoch 148/500\n","5/5 [==============================] - 0s 7ms/step - loss: 15.9396 - mse: 15.9396 - val_loss: 12.2946 - val_mse: 8.9784\n","Epoch 149/500\n","5/5 [==============================] - 0s 7ms/step - loss: 15.8131 - mse: 15.8131 - val_loss: 12.0401 - val_mse: 8.8392\n","Epoch 150/500\n","5/5 [==============================] - 0s 7ms/step - loss: 15.6537 - mse: 15.6537 - val_loss: 11.8125 - val_mse: 8.7166\n","Epoch 151/500\n","5/5 [==============================] - 0s 7ms/step - loss: 15.5217 - mse: 15.5217 - val_loss: 11.5924 - val_mse: 8.5997\n","Epoch 152/500\n","5/5 [==============================] - 0s 8ms/step - loss: 15.3799 - mse: 15.3799 - val_loss: 11.3649 - val_mse: 8.4726\n","Epoch 153/500\n","5/5 [==============================] - 0s 8ms/step - loss: 15.2450 - mse: 15.2450 - val_loss: 11.1566 - val_mse: 8.3631\n","Epoch 154/500\n","5/5 [==============================] - 0s 8ms/step - loss: 15.0846 - mse: 15.0846 - val_loss: 10.9420 - val_mse: 8.2484\n","Epoch 155/500\n","5/5 [==============================] - 0s 8ms/step - loss: 14.9083 - mse: 14.9083 - val_loss: 10.7316 - val_mse: 8.1336\n","Epoch 156/500\n","5/5 [==============================] - 0s 8ms/step - loss: 14.7806 - mse: 14.7806 - val_loss: 10.4970 - val_mse: 8.0163\n","Epoch 157/500\n","5/5 [==============================] - 0s 7ms/step - loss: 14.6094 - mse: 14.6094 - val_loss: 10.2706 - val_mse: 7.8959\n","Epoch 158/500\n","5/5 [==============================] - 0s 8ms/step - loss: 14.4740 - mse: 14.4740 - val_loss: 10.0466 - val_mse: 7.7746\n","Epoch 159/500\n","5/5 [==============================] - 0s 7ms/step - loss: 14.2919 - mse: 14.2919 - val_loss: 9.8523 - val_mse: 7.6706\n","Epoch 160/500\n","5/5 [==============================] - 0s 7ms/step - loss: 14.1891 - mse: 14.1891 - val_loss: 9.6413 - val_mse: 7.5711\n","Epoch 161/500\n","5/5 [==============================] - 0s 9ms/step - loss: 14.0383 - mse: 14.0383 - val_loss: 9.4652 - val_mse: 7.4849\n","Epoch 162/500\n","5/5 [==============================] - 0s 7ms/step - loss: 13.8931 - mse: 13.8931 - val_loss: 9.2879 - val_mse: 7.3921\n","Epoch 163/500\n","5/5 [==============================] - 0s 9ms/step - loss: 13.8171 - mse: 13.8171 - val_loss: 9.0803 - val_mse: 7.2715\n","Epoch 164/500\n","5/5 [==============================] - 0s 7ms/step - loss: 13.6744 - mse: 13.6744 - val_loss: 8.9044 - val_mse: 7.1663\n","Epoch 165/500\n","5/5 [==============================] - 0s 8ms/step - loss: 13.5650 - mse: 13.5650 - val_loss: 8.7320 - val_mse: 7.0530\n","Epoch 166/500\n","5/5 [==============================] - 0s 7ms/step - loss: 13.4560 - mse: 13.4560 - val_loss: 8.5785 - val_mse: 6.9585\n","Epoch 167/500\n","5/5 [==============================] - 0s 8ms/step - loss: 13.3722 - mse: 13.3722 - val_loss: 8.4165 - val_mse: 6.8603\n","Epoch 168/500\n","5/5 [==============================] - 0s 7ms/step - loss: 13.2710 - mse: 13.2710 - val_loss: 8.2742 - val_mse: 6.7785\n","Epoch 169/500\n","5/5 [==============================] - 0s 7ms/step - loss: 13.1897 - mse: 13.1897 - val_loss: 8.1497 - val_mse: 6.7070\n","Epoch 170/500\n","5/5 [==============================] - 0s 9ms/step - loss: 13.1277 - mse: 13.1277 - val_loss: 8.0116 - val_mse: 6.6320\n","Epoch 171/500\n","5/5 [==============================] - 0s 7ms/step - loss: 13.0485 - mse: 13.0485 - val_loss: 7.8847 - val_mse: 6.5624\n","Epoch 172/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.9602 - mse: 12.9602 - val_loss: 7.7739 - val_mse: 6.5028\n","Epoch 173/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.9164 - mse: 12.9164 - val_loss: 7.6550 - val_mse: 6.4228\n","Epoch 174/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.8337 - mse: 12.8337 - val_loss: 7.5548 - val_mse: 6.3777\n","Epoch 175/500\n","5/5 [==============================] - 0s 7ms/step - loss: 12.7660 - mse: 12.7660 - val_loss: 7.4709 - val_mse: 6.3365\n","Epoch 176/500\n","5/5 [==============================] - 0s 9ms/step - loss: 12.7259 - mse: 12.7259 - val_loss: 7.3707 - val_mse: 6.2767\n","Epoch 177/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.6588 - mse: 12.6588 - val_loss: 7.2932 - val_mse: 6.2320\n","Epoch 178/500\n","5/5 [==============================] - 0s 7ms/step - loss: 12.6252 - mse: 12.6252 - val_loss: 7.1974 - val_mse: 6.1731\n","Epoch 179/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.5606 - mse: 12.5606 - val_loss: 7.1299 - val_mse: 6.1359\n","Epoch 180/500\n","5/5 [==============================] - 0s 7ms/step - loss: 12.5207 - mse: 12.5207 - val_loss: 7.0636 - val_mse: 6.1086\n","Epoch 181/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.4800 - mse: 12.4800 - val_loss: 6.9865 - val_mse: 6.0635\n","Epoch 182/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.4516 - mse: 12.4516 - val_loss: 6.9097 - val_mse: 6.0173\n","Epoch 183/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.4010 - mse: 12.4010 - val_loss: 6.8519 - val_mse: 5.9860\n","Epoch 184/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.3694 - mse: 12.3694 - val_loss: 6.7926 - val_mse: 5.9540\n","Epoch 185/500\n","5/5 [==============================] - 0s 7ms/step - loss: 12.3332 - mse: 12.3332 - val_loss: 6.7395 - val_mse: 5.9380\n","Epoch 186/500\n","5/5 [==============================] - 0s 7ms/step - loss: 12.2990 - mse: 12.2990 - val_loss: 6.6984 - val_mse: 5.9157\n","Epoch 187/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.2760 - mse: 12.2760 - val_loss: 6.6613 - val_mse: 5.9042\n","Epoch 188/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.2418 - mse: 12.2418 - val_loss: 6.6278 - val_mse: 5.8846\n","Epoch 189/500\n","5/5 [==============================] - 0s 7ms/step - loss: 12.2232 - mse: 12.2232 - val_loss: 6.5900 - val_mse: 5.8635\n","Epoch 190/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.1994 - mse: 12.1994 - val_loss: 6.5561 - val_mse: 5.8386\n","Epoch 191/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.1903 - mse: 12.1903 - val_loss: 6.5193 - val_mse: 5.8082\n","Epoch 192/500\n","5/5 [==============================] - 0s 9ms/step - loss: 12.1575 - mse: 12.1575 - val_loss: 6.4963 - val_mse: 5.8000\n","Epoch 193/500\n","5/5 [==============================] - 0s 9ms/step - loss: 12.1548 - mse: 12.1548 - val_loss: 6.4731 - val_mse: 5.7684\n","Epoch 194/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.1158 - mse: 12.1158 - val_loss: 6.4501 - val_mse: 5.7570\n","Epoch 195/500\n","5/5 [==============================] - 0s 7ms/step - loss: 12.0990 - mse: 12.0990 - val_loss: 6.4253 - val_mse: 5.7438\n","Epoch 196/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.0722 - mse: 12.0722 - val_loss: 6.4006 - val_mse: 5.7366\n","Epoch 197/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.0580 - mse: 12.0580 - val_loss: 6.3791 - val_mse: 5.7214\n","Epoch 198/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.0320 - mse: 12.0320 - val_loss: 6.3575 - val_mse: 5.7098\n","Epoch 199/500\n","5/5 [==============================] - 0s 8ms/step - loss: 12.0188 - mse: 12.0188 - val_loss: 6.3334 - val_mse: 5.7076\n","Epoch 200/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.9905 - mse: 11.9905 - val_loss: 6.3172 - val_mse: 5.7042\n","Epoch 201/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.9642 - mse: 11.9642 - val_loss: 6.3020 - val_mse: 5.7017\n","Epoch 202/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.9459 - mse: 11.9459 - val_loss: 6.2942 - val_mse: 5.7052\n","Epoch 203/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.9315 - mse: 11.9315 - val_loss: 6.2765 - val_mse: 5.6933\n","Epoch 204/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.9162 - mse: 11.9162 - val_loss: 6.2548 - val_mse: 5.6771\n","Epoch 205/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.8903 - mse: 11.8903 - val_loss: 6.2328 - val_mse: 5.6694\n","Epoch 206/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.8721 - mse: 11.8721 - val_loss: 6.2193 - val_mse: 5.6617\n","Epoch 207/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.8516 - mse: 11.8516 - val_loss: 6.2118 - val_mse: 5.6603\n","Epoch 208/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.8322 - mse: 11.8322 - val_loss: 6.1986 - val_mse: 5.6605\n","Epoch 209/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.8233 - mse: 11.8233 - val_loss: 6.1828 - val_mse: 5.6545\n","Epoch 210/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.7977 - mse: 11.7977 - val_loss: 6.1727 - val_mse: 5.6487\n","Epoch 211/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.7881 - mse: 11.7881 - val_loss: 6.1703 - val_mse: 5.6570\n","Epoch 212/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.7849 - mse: 11.7849 - val_loss: 6.1674 - val_mse: 5.6520\n","Epoch 213/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.7520 - mse: 11.7520 - val_loss: 6.1617 - val_mse: 5.6562\n","Epoch 214/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.7479 - mse: 11.7479 - val_loss: 6.1618 - val_mse: 5.6498\n","Epoch 215/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.7319 - mse: 11.7319 - val_loss: 6.1506 - val_mse: 5.6490\n","Epoch 216/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.7095 - mse: 11.7095 - val_loss: 6.1512 - val_mse: 5.6622\n","Epoch 217/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.6990 - mse: 11.6990 - val_loss: 6.1516 - val_mse: 5.6611\n","Epoch 218/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.6905 - mse: 11.6905 - val_loss: 6.1475 - val_mse: 5.6559\n","Epoch 219/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.6786 - mse: 11.6786 - val_loss: 6.1472 - val_mse: 5.6723\n","Epoch 220/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.6637 - mse: 11.6637 - val_loss: 6.1500 - val_mse: 5.6684\n","Epoch 221/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.6498 - mse: 11.6498 - val_loss: 6.1407 - val_mse: 5.6781\n","Epoch 222/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.6322 - mse: 11.6322 - val_loss: 6.1424 - val_mse: 5.6837\n","Epoch 223/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.6276 - mse: 11.6276 - val_loss: 6.1498 - val_mse: 5.6908\n","Epoch 224/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.6213 - mse: 11.6213 - val_loss: 6.1399 - val_mse: 5.6967\n","Epoch 225/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.5984 - mse: 11.5984 - val_loss: 6.1452 - val_mse: 5.6968\n","Epoch 226/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.5857 - mse: 11.5857 - val_loss: 6.1440 - val_mse: 5.7015\n","Epoch 227/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.5762 - mse: 11.5762 - val_loss: 6.1469 - val_mse: 5.7057\n","Epoch 228/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.5729 - mse: 11.5729 - val_loss: 6.1542 - val_mse: 5.7221\n","Epoch 229/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.5569 - mse: 11.5569 - val_loss: 6.1602 - val_mse: 5.7324\n","Epoch 230/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.5436 - mse: 11.5436 - val_loss: 6.1617 - val_mse: 5.7338\n","Epoch 231/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.5320 - mse: 11.5320 - val_loss: 6.1690 - val_mse: 5.7327\n","Epoch 232/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.5238 - mse: 11.5238 - val_loss: 6.1813 - val_mse: 5.7335\n","Epoch 233/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.5224 - mse: 11.5224 - val_loss: 6.1830 - val_mse: 5.7504\n","Epoch 234/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.5037 - mse: 11.5037 - val_loss: 6.1945 - val_mse: 5.7498\n","Epoch 235/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.4871 - mse: 11.4871 - val_loss: 6.1995 - val_mse: 5.7609\n","Epoch 236/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.4951 - mse: 11.4951 - val_loss: 6.2069 - val_mse: 5.7577\n","Epoch 237/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.4542 - mse: 11.4542 - val_loss: 6.2069 - val_mse: 5.7665\n","Epoch 238/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.4332 - mse: 11.4332 - val_loss: 6.2136 - val_mse: 5.7577\n","Epoch 239/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.4200 - mse: 11.4200 - val_loss: 6.2256 - val_mse: 5.7557\n","Epoch 240/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.4029 - mse: 11.4029 - val_loss: 6.2304 - val_mse: 5.7590\n","Epoch 241/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.3986 - mse: 11.3986 - val_loss: 6.2300 - val_mse: 5.7460\n","Epoch 242/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.3746 - mse: 11.3746 - val_loss: 6.2437 - val_mse: 5.7619\n","Epoch 243/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.3553 - mse: 11.3553 - val_loss: 6.2452 - val_mse: 5.7739\n","Epoch 244/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.3499 - mse: 11.3499 - val_loss: 6.2542 - val_mse: 5.7855\n","Epoch 245/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.3347 - mse: 11.3347 - val_loss: 6.2580 - val_mse: 5.7854\n","Epoch 246/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.3217 - mse: 11.3217 - val_loss: 6.2559 - val_mse: 5.7978\n","Epoch 247/500\n","5/5 [==============================] - 0s 10ms/step - loss: 11.3137 - mse: 11.3137 - val_loss: 6.2655 - val_mse: 5.8153\n","Epoch 248/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.3032 - mse: 11.3032 - val_loss: 6.2777 - val_mse: 5.8169\n","Epoch 249/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.2898 - mse: 11.2898 - val_loss: 6.2852 - val_mse: 5.8236\n","Epoch 250/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.2769 - mse: 11.2769 - val_loss: 6.2900 - val_mse: 5.8363\n","Epoch 251/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.2768 - mse: 11.2768 - val_loss: 6.2901 - val_mse: 5.8563\n","Epoch 252/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.2615 - mse: 11.2615 - val_loss: 6.2976 - val_mse: 5.8665\n","Epoch 253/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.2544 - mse: 11.2544 - val_loss: 6.3027 - val_mse: 5.8820\n","Epoch 254/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.2445 - mse: 11.2445 - val_loss: 6.3066 - val_mse: 5.8868\n","Epoch 255/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.2349 - mse: 11.2349 - val_loss: 6.3161 - val_mse: 5.8850\n","Epoch 256/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.2301 - mse: 11.2301 - val_loss: 6.3256 - val_mse: 5.9056\n","Epoch 257/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.2217 - mse: 11.2217 - val_loss: 6.3353 - val_mse: 5.9078\n","Epoch 258/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.2131 - mse: 11.2131 - val_loss: 6.3432 - val_mse: 5.9062\n","Epoch 259/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.2004 - mse: 11.2004 - val_loss: 6.3554 - val_mse: 5.9203\n","Epoch 260/500\n","5/5 [==============================] - 0s 10ms/step - loss: 11.2029 - mse: 11.2029 - val_loss: 6.3626 - val_mse: 5.9263\n","Epoch 261/500\n","5/5 [==============================] - 0s 10ms/step - loss: 11.1824 - mse: 11.1824 - val_loss: 6.3653 - val_mse: 5.9373\n","Epoch 262/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.1774 - mse: 11.1774 - val_loss: 6.3774 - val_mse: 5.9538\n","Epoch 263/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.1778 - mse: 11.1778 - val_loss: 6.3884 - val_mse: 5.9808\n","Epoch 264/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.1620 - mse: 11.1620 - val_loss: 6.3956 - val_mse: 5.9887\n","Epoch 265/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.1597 - mse: 11.1597 - val_loss: 6.4011 - val_mse: 5.9857\n","Epoch 266/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.1553 - mse: 11.1553 - val_loss: 6.4181 - val_mse: 6.0046\n","Epoch 267/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.1523 - mse: 11.1523 - val_loss: 6.4228 - val_mse: 6.0020\n","Epoch 268/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.1402 - mse: 11.1402 - val_loss: 6.4305 - val_mse: 6.0013\n","Epoch 269/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.1347 - mse: 11.1347 - val_loss: 6.4405 - val_mse: 6.0268\n","Epoch 270/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.1229 - mse: 11.1229 - val_loss: 6.4493 - val_mse: 6.0377\n","Epoch 271/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.1197 - mse: 11.1197 - val_loss: 6.4642 - val_mse: 6.0528\n","Epoch 272/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.1187 - mse: 11.1187 - val_loss: 6.4646 - val_mse: 6.0678\n","Epoch 273/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.1058 - mse: 11.1058 - val_loss: 6.4744 - val_mse: 6.0744\n","Epoch 274/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.1040 - mse: 11.1040 - val_loss: 6.4865 - val_mse: 6.0752\n","Epoch 275/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.0943 - mse: 11.0943 - val_loss: 6.4940 - val_mse: 6.0833\n","Epoch 276/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0883 - mse: 11.0883 - val_loss: 6.5005 - val_mse: 6.1038\n","Epoch 277/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0868 - mse: 11.0868 - val_loss: 6.5084 - val_mse: 6.1012\n","Epoch 278/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.0807 - mse: 11.0807 - val_loss: 6.5137 - val_mse: 6.1199\n","Epoch 279/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.0736 - mse: 11.0736 - val_loss: 6.5240 - val_mse: 6.1310\n","Epoch 280/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.0805 - mse: 11.0805 - val_loss: 6.5386 - val_mse: 6.1312\n","Epoch 281/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0621 - mse: 11.0621 - val_loss: 6.5522 - val_mse: 6.1497\n","Epoch 282/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.0544 - mse: 11.0544 - val_loss: 6.5570 - val_mse: 6.1614\n","Epoch 283/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.0585 - mse: 11.0585 - val_loss: 6.5735 - val_mse: 6.1721\n","Epoch 284/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.0493 - mse: 11.0493 - val_loss: 6.5830 - val_mse: 6.1770\n","Epoch 285/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0426 - mse: 11.0426 - val_loss: 6.5909 - val_mse: 6.1816\n","Epoch 286/500\n","5/5 [==============================] - 0s 10ms/step - loss: 11.0393 - mse: 11.0393 - val_loss: 6.6073 - val_mse: 6.1997\n","Epoch 287/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0320 - mse: 11.0320 - val_loss: 6.6109 - val_mse: 6.2147\n","Epoch 288/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0290 - mse: 11.0290 - val_loss: 6.6182 - val_mse: 6.2258\n","Epoch 289/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.0266 - mse: 11.0266 - val_loss: 6.6184 - val_mse: 6.2340\n","Epoch 290/500\n","5/5 [==============================] - 0s 9ms/step - loss: 11.0261 - mse: 11.0261 - val_loss: 6.6302 - val_mse: 6.2444\n","Epoch 291/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0172 - mse: 11.0172 - val_loss: 6.6438 - val_mse: 6.2572\n","Epoch 292/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0118 - mse: 11.0118 - val_loss: 6.6557 - val_mse: 6.2622\n","Epoch 293/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0066 - mse: 11.0066 - val_loss: 6.6633 - val_mse: 6.2661\n","Epoch 294/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0044 - mse: 11.0044 - val_loss: 6.6693 - val_mse: 6.2765\n","Epoch 295/500\n","5/5 [==============================] - 0s 8ms/step - loss: 11.0003 - mse: 11.0003 - val_loss: 6.6793 - val_mse: 6.2957\n","Epoch 296/500\n","5/5 [==============================] - 0s 7ms/step - loss: 11.0040 - mse: 11.0040 - val_loss: 6.6953 - val_mse: 6.3179\n","Epoch 297/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9945 - mse: 10.9945 - val_loss: 6.6995 - val_mse: 6.3277\n","Epoch 298/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9907 - mse: 10.9907 - val_loss: 6.7068 - val_mse: 6.3344\n","Epoch 299/500\n","5/5 [==============================] - 0s 10ms/step - loss: 10.9868 - mse: 10.9868 - val_loss: 6.7192 - val_mse: 6.3357\n","Epoch 300/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9898 - mse: 10.9898 - val_loss: 6.7311 - val_mse: 6.3355\n","Epoch 301/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9890 - mse: 10.9890 - val_loss: 6.7363 - val_mse: 6.3405\n","Epoch 302/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9745 - mse: 10.9745 - val_loss: 6.7444 - val_mse: 6.3536\n","Epoch 303/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.9763 - mse: 10.9763 - val_loss: 6.7506 - val_mse: 6.3659\n","Epoch 304/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9684 - mse: 10.9684 - val_loss: 6.7559 - val_mse: 6.3759\n","Epoch 305/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9704 - mse: 10.9704 - val_loss: 6.7642 - val_mse: 6.3863\n","Epoch 306/500\n","5/5 [==============================] - 0s 11ms/step - loss: 10.9742 - mse: 10.9742 - val_loss: 6.7771 - val_mse: 6.3939\n","Epoch 307/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9641 - mse: 10.9641 - val_loss: 6.7883 - val_mse: 6.4096\n","Epoch 308/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.9690 - mse: 10.9690 - val_loss: 6.7969 - val_mse: 6.4103\n","Epoch 309/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9605 - mse: 10.9605 - val_loss: 6.7998 - val_mse: 6.4172\n","Epoch 310/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9553 - mse: 10.9553 - val_loss: 6.8175 - val_mse: 6.4390\n","Epoch 311/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9468 - mse: 10.9468 - val_loss: 6.8279 - val_mse: 6.4571\n","Epoch 312/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9447 - mse: 10.9447 - val_loss: 6.8361 - val_mse: 6.4729\n","Epoch 313/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9449 - mse: 10.9449 - val_loss: 6.8446 - val_mse: 6.4842\n","Epoch 314/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9437 - mse: 10.9437 - val_loss: 6.8509 - val_mse: 6.4987\n","Epoch 315/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9379 - mse: 10.9379 - val_loss: 6.8631 - val_mse: 6.5059\n","Epoch 316/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9412 - mse: 10.9412 - val_loss: 6.8713 - val_mse: 6.5121\n","Epoch 317/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9345 - mse: 10.9345 - val_loss: 6.8727 - val_mse: 6.5163\n","Epoch 318/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.9318 - mse: 10.9318 - val_loss: 6.8869 - val_mse: 6.5253\n","Epoch 319/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9290 - mse: 10.9290 - val_loss: 6.8891 - val_mse: 6.5357\n","Epoch 320/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9247 - mse: 10.9247 - val_loss: 6.8959 - val_mse: 6.5426\n","Epoch 321/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9355 - mse: 10.9355 - val_loss: 6.8971 - val_mse: 6.5552\n","Epoch 322/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9239 - mse: 10.9239 - val_loss: 6.9090 - val_mse: 6.5653\n","Epoch 323/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9253 - mse: 10.9253 - val_loss: 6.9212 - val_mse: 6.5681\n","Epoch 324/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.9205 - mse: 10.9205 - val_loss: 6.9330 - val_mse: 6.5753\n","Epoch 325/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9213 - mse: 10.9213 - val_loss: 6.9433 - val_mse: 6.5845\n","Epoch 326/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9202 - mse: 10.9202 - val_loss: 6.9501 - val_mse: 6.5939\n","Epoch 327/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9174 - mse: 10.9174 - val_loss: 6.9588 - val_mse: 6.6099\n","Epoch 328/500\n","5/5 [==============================] - 0s 10ms/step - loss: 10.9157 - mse: 10.9157 - val_loss: 6.9696 - val_mse: 6.6125\n","Epoch 329/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9110 - mse: 10.9110 - val_loss: 6.9792 - val_mse: 6.6186\n","Epoch 330/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9123 - mse: 10.9123 - val_loss: 6.9873 - val_mse: 6.6251\n","Epoch 331/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9079 - mse: 10.9079 - val_loss: 6.9865 - val_mse: 6.6427\n","Epoch 332/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9041 - mse: 10.9041 - val_loss: 6.9951 - val_mse: 6.6588\n","Epoch 333/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9024 - mse: 10.9024 - val_loss: 7.0059 - val_mse: 6.6588\n","Epoch 334/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9024 - mse: 10.9024 - val_loss: 7.0107 - val_mse: 6.6580\n","Epoch 335/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.9024 - mse: 10.9024 - val_loss: 7.0164 - val_mse: 6.6746\n","Epoch 336/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.9086 - mse: 10.9086 - val_loss: 7.0240 - val_mse: 6.6942\n","Epoch 337/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8964 - mse: 10.8964 - val_loss: 7.0262 - val_mse: 6.7027\n","Epoch 338/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8965 - mse: 10.8965 - val_loss: 7.0402 - val_mse: 6.7068\n","Epoch 339/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8920 - mse: 10.8920 - val_loss: 7.0467 - val_mse: 6.7183\n","Epoch 340/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8964 - mse: 10.8964 - val_loss: 7.0517 - val_mse: 6.7301\n","Epoch 341/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8938 - mse: 10.8938 - val_loss: 7.0588 - val_mse: 6.7404\n","Epoch 342/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8923 - mse: 10.8923 - val_loss: 7.0739 - val_mse: 6.7396\n","Epoch 343/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8863 - mse: 10.8863 - val_loss: 7.0753 - val_mse: 6.7477\n","Epoch 344/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8867 - mse: 10.8867 - val_loss: 7.0804 - val_mse: 6.7509\n","Epoch 345/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8882 - mse: 10.8882 - val_loss: 7.0892 - val_mse: 6.7575\n","Epoch 346/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8822 - mse: 10.8822 - val_loss: 7.0934 - val_mse: 6.7631\n","Epoch 347/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.9005 - mse: 10.9005 - val_loss: 7.1049 - val_mse: 6.7478\n","Epoch 348/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8804 - mse: 10.8804 - val_loss: 7.1044 - val_mse: 6.7547\n","Epoch 349/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8783 - mse: 10.8783 - val_loss: 7.1158 - val_mse: 6.7698\n","Epoch 350/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8811 - mse: 10.8811 - val_loss: 7.1186 - val_mse: 6.7805\n","Epoch 351/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8798 - mse: 10.8798 - val_loss: 7.1236 - val_mse: 6.7866\n","Epoch 352/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8802 - mse: 10.8802 - val_loss: 7.1304 - val_mse: 6.7906\n","Epoch 353/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8750 - mse: 10.8750 - val_loss: 7.1387 - val_mse: 6.7974\n","Epoch 354/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8723 - mse: 10.8723 - val_loss: 7.1485 - val_mse: 6.8033\n","Epoch 355/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8724 - mse: 10.8724 - val_loss: 7.1539 - val_mse: 6.8098\n","Epoch 356/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8732 - mse: 10.8732 - val_loss: 7.1606 - val_mse: 6.8225\n","Epoch 357/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8712 - mse: 10.8712 - val_loss: 7.1621 - val_mse: 6.8342\n","Epoch 358/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8684 - mse: 10.8684 - val_loss: 7.1654 - val_mse: 6.8407\n","Epoch 359/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8695 - mse: 10.8695 - val_loss: 7.1791 - val_mse: 6.8495\n","Epoch 360/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8672 - mse: 10.8672 - val_loss: 7.1836 - val_mse: 6.8646\n","Epoch 361/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8642 - mse: 10.8642 - val_loss: 7.1861 - val_mse: 6.8720\n","Epoch 362/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8763 - mse: 10.8763 - val_loss: 7.1900 - val_mse: 6.8557\n","Epoch 363/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8663 - mse: 10.8663 - val_loss: 7.1939 - val_mse: 6.8645\n","Epoch 364/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8655 - mse: 10.8655 - val_loss: 7.1964 - val_mse: 6.8803\n","Epoch 365/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8648 - mse: 10.8648 - val_loss: 7.2035 - val_mse: 6.8842\n","Epoch 366/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8620 - mse: 10.8620 - val_loss: 7.2112 - val_mse: 6.8930\n","Epoch 367/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8624 - mse: 10.8624 - val_loss: 7.2090 - val_mse: 6.8918\n","Epoch 368/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8608 - mse: 10.8608 - val_loss: 7.2089 - val_mse: 6.9047\n","Epoch 369/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8612 - mse: 10.8612 - val_loss: 7.2154 - val_mse: 6.9168\n","Epoch 370/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8600 - mse: 10.8600 - val_loss: 7.2228 - val_mse: 6.9095\n","Epoch 371/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8698 - mse: 10.8698 - val_loss: 7.2358 - val_mse: 6.9137\n","Epoch 372/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8555 - mse: 10.8555 - val_loss: 7.2441 - val_mse: 6.9179\n","Epoch 373/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8602 - mse: 10.8602 - val_loss: 7.2516 - val_mse: 6.9205\n","Epoch 374/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8643 - mse: 10.8643 - val_loss: 7.2516 - val_mse: 6.9404\n","Epoch 375/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8632 - mse: 10.8632 - val_loss: 7.2571 - val_mse: 6.9483\n","Epoch 376/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8538 - mse: 10.8538 - val_loss: 7.2615 - val_mse: 6.9485\n","Epoch 377/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8634 - mse: 10.8634 - val_loss: 7.2536 - val_mse: 6.9596\n","Epoch 378/500\n","5/5 [==============================] - 0s 10ms/step - loss: 10.8675 - mse: 10.8675 - val_loss: 7.2646 - val_mse: 6.9439\n","Epoch 379/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8553 - mse: 10.8553 - val_loss: 7.2670 - val_mse: 6.9578\n","Epoch 380/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8499 - mse: 10.8499 - val_loss: 7.2721 - val_mse: 6.9657\n","Epoch 381/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8583 - mse: 10.8583 - val_loss: 7.2726 - val_mse: 6.9867\n","Epoch 382/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8496 - mse: 10.8496 - val_loss: 7.2750 - val_mse: 6.9906\n","Epoch 383/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8509 - mse: 10.8509 - val_loss: 7.2899 - val_mse: 6.9902\n","Epoch 384/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8579 - mse: 10.8579 - val_loss: 7.2932 - val_mse: 7.0082\n","Epoch 385/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8499 - mse: 10.8499 - val_loss: 7.3006 - val_mse: 6.9979\n","Epoch 386/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8449 - mse: 10.8449 - val_loss: 7.2977 - val_mse: 6.9988\n","Epoch 387/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8508 - mse: 10.8508 - val_loss: 7.3111 - val_mse: 7.0000\n","Epoch 388/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8450 - mse: 10.8450 - val_loss: 7.3099 - val_mse: 7.0102\n","Epoch 389/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8480 - mse: 10.8480 - val_loss: 7.3107 - val_mse: 7.0046\n","Epoch 390/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8448 - mse: 10.8448 - val_loss: 7.3111 - val_mse: 7.0143\n","Epoch 391/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8440 - mse: 10.8440 - val_loss: 7.3171 - val_mse: 7.0117\n","Epoch 392/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8434 - mse: 10.8434 - val_loss: 7.3162 - val_mse: 7.0156\n","Epoch 393/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8410 - mse: 10.8410 - val_loss: 7.3219 - val_mse: 7.0192\n","Epoch 394/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8388 - mse: 10.8388 - val_loss: 7.3317 - val_mse: 7.0293\n","Epoch 395/500\n","5/5 [==============================] - 0s 10ms/step - loss: 10.8440 - mse: 10.8440 - val_loss: 7.3409 - val_mse: 7.0395\n","Epoch 396/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8426 - mse: 10.8426 - val_loss: 7.3357 - val_mse: 7.0398\n","Epoch 397/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8386 - mse: 10.8386 - val_loss: 7.3360 - val_mse: 7.0416\n","Epoch 398/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8495 - mse: 10.8495 - val_loss: 7.3383 - val_mse: 7.0658\n","Epoch 399/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8420 - mse: 10.8420 - val_loss: 7.3490 - val_mse: 7.0677\n","Epoch 400/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8387 - mse: 10.8387 - val_loss: 7.3465 - val_mse: 7.0614\n","Epoch 401/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8363 - mse: 10.8363 - val_loss: 7.3469 - val_mse: 7.0528\n","Epoch 402/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8399 - mse: 10.8399 - val_loss: 7.3529 - val_mse: 7.0509\n","Epoch 403/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8369 - mse: 10.8369 - val_loss: 7.3567 - val_mse: 7.0592\n","Epoch 404/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8375 - mse: 10.8375 - val_loss: 7.3679 - val_mse: 7.0687\n","Epoch 405/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8366 - mse: 10.8366 - val_loss: 7.3739 - val_mse: 7.0854\n","Epoch 406/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8401 - mse: 10.8401 - val_loss: 7.3713 - val_mse: 7.0916\n","Epoch 407/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8442 - mse: 10.8442 - val_loss: 7.3860 - val_mse: 7.0901\n","Epoch 408/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8429 - mse: 10.8429 - val_loss: 7.3914 - val_mse: 7.0799\n","Epoch 409/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8366 - mse: 10.8366 - val_loss: 7.3914 - val_mse: 7.0812\n","Epoch 410/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8406 - mse: 10.8406 - val_loss: 7.3888 - val_mse: 7.1088\n","Epoch 411/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8317 - mse: 10.8317 - val_loss: 7.3823 - val_mse: 7.1070\n","Epoch 412/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8362 - mse: 10.8362 - val_loss: 7.3856 - val_mse: 7.1219\n","Epoch 413/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8410 - mse: 10.8410 - val_loss: 7.3846 - val_mse: 7.1331\n","Epoch 414/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8347 - mse: 10.8347 - val_loss: 7.3911 - val_mse: 7.1327\n","Epoch 415/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8314 - mse: 10.8314 - val_loss: 7.3994 - val_mse: 7.1260\n","Epoch 416/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8431 - mse: 10.8431 - val_loss: 7.3926 - val_mse: 7.1131\n","Epoch 417/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8330 - mse: 10.8330 - val_loss: 7.3992 - val_mse: 7.1135\n","Epoch 418/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8340 - mse: 10.8340 - val_loss: 7.4091 - val_mse: 7.1159\n","Epoch 419/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8307 - mse: 10.8307 - val_loss: 7.4112 - val_mse: 7.1237\n","Epoch 420/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8290 - mse: 10.8290 - val_loss: 7.4092 - val_mse: 7.1271\n","Epoch 421/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8323 - mse: 10.8323 - val_loss: 7.4084 - val_mse: 7.1276\n","Epoch 422/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8268 - mse: 10.8268 - val_loss: 7.4115 - val_mse: 7.1307\n","Epoch 423/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8258 - mse: 10.8258 - val_loss: 7.4131 - val_mse: 7.1277\n","Epoch 424/500\n","5/5 [==============================] - 0s 11ms/step - loss: 10.8309 - mse: 10.8309 - val_loss: 7.4201 - val_mse: 7.1412\n","Epoch 425/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8237 - mse: 10.8237 - val_loss: 7.4172 - val_mse: 7.1504\n","Epoch 426/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8267 - mse: 10.8267 - val_loss: 7.4289 - val_mse: 7.1580\n","Epoch 427/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8303 - mse: 10.8303 - val_loss: 7.4275 - val_mse: 7.1588\n","Epoch 428/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8329 - mse: 10.8329 - val_loss: 7.4381 - val_mse: 7.1675\n","Epoch 429/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8258 - mse: 10.8258 - val_loss: 7.4335 - val_mse: 7.1640\n","Epoch 430/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8240 - mse: 10.8240 - val_loss: 7.4384 - val_mse: 7.1734\n","Epoch 431/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8254 - mse: 10.8254 - val_loss: 7.4448 - val_mse: 7.1878\n","Epoch 432/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8257 - mse: 10.8257 - val_loss: 7.4403 - val_mse: 7.1892\n","Epoch 433/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8293 - mse: 10.8293 - val_loss: 7.4392 - val_mse: 7.1740\n","Epoch 434/500\n","5/5 [==============================] - 0s 10ms/step - loss: 10.8211 - mse: 10.8211 - val_loss: 7.4430 - val_mse: 7.1781\n","Epoch 435/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8303 - mse: 10.8303 - val_loss: 7.4481 - val_mse: 7.1701\n","Epoch 436/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8242 - mse: 10.8242 - val_loss: 7.4574 - val_mse: 7.1760\n","Epoch 437/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8218 - mse: 10.8218 - val_loss: 7.4561 - val_mse: 7.1730\n","Epoch 438/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8241 - mse: 10.8241 - val_loss: 7.4553 - val_mse: 7.1806\n","Epoch 439/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8351 - mse: 10.8351 - val_loss: 7.4581 - val_mse: 7.2052\n","Epoch 440/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8258 - mse: 10.8258 - val_loss: 7.4616 - val_mse: 7.1913\n","Epoch 441/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8235 - mse: 10.8235 - val_loss: 7.4668 - val_mse: 7.1896\n","Epoch 442/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8178 - mse: 10.8178 - val_loss: 7.4701 - val_mse: 7.1916\n","Epoch 443/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8200 - mse: 10.8200 - val_loss: 7.4690 - val_mse: 7.2029\n","Epoch 444/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8165 - mse: 10.8165 - val_loss: 7.4680 - val_mse: 7.2030\n","Epoch 445/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8196 - mse: 10.8196 - val_loss: 7.4684 - val_mse: 7.2128\n","Epoch 446/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8187 - mse: 10.8187 - val_loss: 7.4731 - val_mse: 7.2134\n","Epoch 447/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8204 - mse: 10.8204 - val_loss: 7.4750 - val_mse: 7.2280\n","Epoch 448/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8168 - mse: 10.8168 - val_loss: 7.4726 - val_mse: 7.2223\n","Epoch 449/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8190 - mse: 10.8190 - val_loss: 7.4789 - val_mse: 7.2332\n","Epoch 450/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8230 - mse: 10.8230 - val_loss: 7.4761 - val_mse: 7.2164\n","Epoch 451/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8137 - mse: 10.8137 - val_loss: 7.4790 - val_mse: 7.2234\n","Epoch 452/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8153 - mse: 10.8153 - val_loss: 7.4798 - val_mse: 7.2309\n","Epoch 453/500\n","5/5 [==============================] - 0s 10ms/step - loss: 10.8171 - mse: 10.8171 - val_loss: 7.4776 - val_mse: 7.2274\n","Epoch 454/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8122 - mse: 10.8122 - val_loss: 7.4823 - val_mse: 7.2308\n","Epoch 455/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8211 - mse: 10.8211 - val_loss: 7.4778 - val_mse: 7.2305\n","Epoch 456/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8220 - mse: 10.8220 - val_loss: 7.4778 - val_mse: 7.2405\n","Epoch 457/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8165 - mse: 10.8165 - val_loss: 7.4906 - val_mse: 7.2338\n","Epoch 458/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8410 - mse: 10.8410 - val_loss: 7.4926 - val_mse: 7.2566\n","Epoch 459/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8120 - mse: 10.8120 - val_loss: 7.4922 - val_mse: 7.2534\n","Epoch 460/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8160 - mse: 10.8160 - val_loss: 7.4953 - val_mse: 7.2366\n","Epoch 461/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8163 - mse: 10.8163 - val_loss: 7.5036 - val_mse: 7.2399\n","Epoch 462/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8120 - mse: 10.8120 - val_loss: 7.5064 - val_mse: 7.2386\n","Epoch 463/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8120 - mse: 10.8120 - val_loss: 7.5066 - val_mse: 7.2366\n","Epoch 464/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8124 - mse: 10.8124 - val_loss: 7.5100 - val_mse: 7.2431\n","Epoch 465/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8180 - mse: 10.8180 - val_loss: 7.5182 - val_mse: 7.2530\n","Epoch 466/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8124 - mse: 10.8124 - val_loss: 7.5178 - val_mse: 7.2615\n","Epoch 467/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8111 - mse: 10.8111 - val_loss: 7.5210 - val_mse: 7.2620\n","Epoch 468/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8084 - mse: 10.8084 - val_loss: 7.5145 - val_mse: 7.2595\n","Epoch 469/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8178 - mse: 10.8178 - val_loss: 7.5122 - val_mse: 7.2491\n","Epoch 470/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8081 - mse: 10.8081 - val_loss: 7.5124 - val_mse: 7.2581\n","Epoch 471/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8135 - mse: 10.8135 - val_loss: 7.5100 - val_mse: 7.2624\n","Epoch 472/500\n","5/5 [==============================] - 0s 13ms/step - loss: 10.8165 - mse: 10.8165 - val_loss: 7.5076 - val_mse: 7.2583\n","Epoch 473/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8114 - mse: 10.8114 - val_loss: 7.5110 - val_mse: 7.2666\n","Epoch 474/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8141 - mse: 10.8141 - val_loss: 7.5109 - val_mse: 7.2594\n","Epoch 475/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8271 - mse: 10.8271 - val_loss: 7.5214 - val_mse: 7.2865\n","Epoch 476/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8071 - mse: 10.8071 - val_loss: 7.5218 - val_mse: 7.2859\n","Epoch 477/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8087 - mse: 10.8087 - val_loss: 7.5212 - val_mse: 7.2788\n","Epoch 478/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8075 - mse: 10.8075 - val_loss: 7.5257 - val_mse: 7.2915\n","Epoch 479/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8049 - mse: 10.8049 - val_loss: 7.5277 - val_mse: 7.2929\n","Epoch 480/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8059 - mse: 10.8059 - val_loss: 7.5262 - val_mse: 7.2915\n","Epoch 481/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8128 - mse: 10.8128 - val_loss: 7.5292 - val_mse: 7.2958\n","Epoch 482/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8091 - mse: 10.8091 - val_loss: 7.5318 - val_mse: 7.2964\n","Epoch 483/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8056 - mse: 10.8056 - val_loss: 7.5274 - val_mse: 7.2908\n","Epoch 484/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8093 - mse: 10.8093 - val_loss: 7.5231 - val_mse: 7.2847\n","Epoch 485/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8027 - mse: 10.8027 - val_loss: 7.5274 - val_mse: 7.2820\n","Epoch 486/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8055 - mse: 10.8055 - val_loss: 7.5321 - val_mse: 7.2890\n","Epoch 487/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8062 - mse: 10.8062 - val_loss: 7.5368 - val_mse: 7.2821\n","Epoch 488/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8055 - mse: 10.8055 - val_loss: 7.5391 - val_mse: 7.2837\n","Epoch 489/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8225 - mse: 10.8225 - val_loss: 7.5533 - val_mse: 7.2762\n","Epoch 490/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8094 - mse: 10.8094 - val_loss: 7.5435 - val_mse: 7.2868\n","Epoch 491/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8068 - mse: 10.8068 - val_loss: 7.5439 - val_mse: 7.2904\n","Epoch 492/500\n","5/5 [==============================] - 0s 9ms/step - loss: 10.8062 - mse: 10.8062 - val_loss: 7.5449 - val_mse: 7.2856\n","Epoch 493/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8025 - mse: 10.8025 - val_loss: 7.5446 - val_mse: 7.2967\n","Epoch 494/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8064 - mse: 10.8064 - val_loss: 7.5472 - val_mse: 7.3107\n","Epoch 495/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8010 - mse: 10.8010 - val_loss: 7.5510 - val_mse: 7.3206\n","Epoch 496/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8053 - mse: 10.8053 - val_loss: 7.5456 - val_mse: 7.3241\n","Epoch 497/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8039 - mse: 10.8039 - val_loss: 7.5508 - val_mse: 7.3223\n","Epoch 498/500\n","5/5 [==============================] - 0s 8ms/step - loss: 10.8038 - mse: 10.8038 - val_loss: 7.5473 - val_mse: 7.3203\n","Epoch 499/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8014 - mse: 10.8014 - val_loss: 7.5405 - val_mse: 7.3211\n","Epoch 500/500\n","5/5 [==============================] - 0s 7ms/step - loss: 10.8058 - mse: 10.8058 - val_loss: 7.5461 - val_mse: 7.3048\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"xoXD1_9VMNAX"},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"YqGJK3dTMbF7"},"source":["# Visualize results"]},{"cell_type":"code","metadata":{"id":"ELWRnDGiMcTt"},"source":["import utilities.simpleplots as sp"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"k5hJ3NZnMjdV","colab":{"base_uri":"https://localhost:8080/","height":292},"executionInfo":{"status":"ok","timestamp":1586211204407,"user_tz":240,"elapsed":492,"user":{"displayName":"Chitta Ranjan","photoUrl":"","userId":"03244148267376825421"}},"outputId":"0bb9e787-0625-4dce-8a78-cd4d80dba464"},"source":["plt, fig = sp.plot_metric(model_history=history, metric='loss')"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAYwAAAETCAYAAAAlCTHcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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44Lp2CJYam0I0QDkr0h4nEajcM+gtuw5Xs53u3Ival9ajUKAsfpzT0b7SF6b1J2M9pF8tT2Hv3z6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\nAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]}]}