tutorial_regression_data.ipynb

      "Epoch 283/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 6.0421e-04 - mean_absolute_percentage_error: 269147.2500 - mean_absolute_error: 0.0183 - mean_squared_error: 6.0421e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29834.5254 - mean_absolute_error: 0.0209 - mean_squared_error: 0.0037 - val_loss: 8.8796e-04 - val_mean_absolute_percentage_error: 64.0319 - val_mean_absolute_error: 0.0199 - val_mean_squared_error: 8.8796e-04\n",
      "Epoch 284/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.2186e-04 - mean_absolute_percentage_error: 29.7772 - mean_absolute_error: 0.0164 - mean_squared_error: 6.2186e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29567.1699 - mean_absolute_error: 0.0209 - mean_squared_error: 0.0037 - val_loss: 8.8445e-04 - val_mean_absolute_percentage_error: 64.5456 - val_mean_absolute_error: 0.0197 - val_mean_squared_error: 8.8445e-04\n",
      "Epoch 285/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.9182e-04 - mean_absolute_percentage_error: 36.9553 - mean_absolute_error: 0.0184 - mean_squared_error: 6.9182e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29996.5371 - mean_absolute_error: 0.0209 - mean_squared_error: 0.0037 - val_loss: 8.7953e-04 - val_mean_absolute_percentage_error: 64.6457 - val_mean_absolute_error: 0.0197 - val_mean_squared_error: 8.7953e-04\n",
      "Epoch 286/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0051 - mean_absolute_percentage_error: 40.5240 - mean_absolute_error: 0.0345 - mean_squared_error: 0.0051",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30672.3711 - mean_absolute_error: 0.0210 - mean_squared_error: 0.0037 - val_loss: 8.9098e-04 - val_mean_absolute_percentage_error: 65.6023 - val_mean_absolute_error: 0.0198 - val_mean_squared_error: 8.9098e-04\n",
      "Epoch 287/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.0178e-04 - mean_absolute_percentage_error: 37.6865 - mean_absolute_error: 0.0104 - mean_squared_error: 2.0178e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 182us/sample - loss: 0.0037 - mean_absolute_percentage_error: 31023.8555 - mean_absolute_error: 0.0212 - mean_squared_error: 0.0037 - val_loss: 8.8938e-04 - val_mean_absolute_percentage_error: 65.6187 - val_mean_absolute_error: 0.0197 - val_mean_squared_error: 8.8938e-04\n",
      "Epoch 288/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0031 - mean_absolute_percentage_error: 278311.1875 - mean_absolute_error: 0.0234 - mean_squared_error: 0.0031",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30850.1895 - mean_absolute_error: 0.0211 - mean_squared_error: 0.0037 - val_loss: 8.8251e-04 - val_mean_absolute_percentage_error: 64.8693 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 8.8251e-04\n",
      "Epoch 289/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.7827e-04 - mean_absolute_percentage_error: 41.0520 - mean_absolute_error: 0.0189 - mean_squared_error: 6.7827e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 202us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30470.2207 - mean_absolute_error: 0.0210 - mean_squared_error: 0.0037 - val_loss: 8.7980e-04 - val_mean_absolute_percentage_error: 64.6269 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 8.7980e-04\n",
      "Epoch 290/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.7711e-04 - mean_absolute_percentage_error: 31.2861 - mean_absolute_error: 0.0170 - mean_squared_error: 4.7711e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 205us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30315.5840 - mean_absolute_error: 0.0211 - mean_squared_error: 0.0037 - val_loss: 8.6514e-04 - val_mean_absolute_percentage_error: 64.1572 - val_mean_absolute_error: 0.0194 - val_mean_squared_error: 8.6514e-04\n",
      "Epoch 291/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.6841e-04 - mean_absolute_percentage_error: 33.7508 - mean_absolute_error: 0.0145 - mean_squared_error: 3.6841e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30130.8125 - mean_absolute_error: 0.0210 - mean_squared_error: 0.0037 - val_loss: 8.6204e-04 - val_mean_absolute_percentage_error: 64.0436 - val_mean_absolute_error: 0.0194 - val_mean_squared_error: 8.6204e-04\n",
      "Epoch 292/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 4.0041e-04 - mean_absolute_percentage_error: 32.6381 - mean_absolute_error: 0.0145 - mean_squared_error: 4.0041e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30329.4746 - mean_absolute_error: 0.0210 - mean_squared_error: 0.0037 - val_loss: 8.7745e-04 - val_mean_absolute_percentage_error: 64.5686 - val_mean_absolute_error: 0.0195 - val_mean_squared_error: 8.7745e-04\n",
      "Epoch 293/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.2405e-04 - mean_absolute_percentage_error: 23.1393 - mean_absolute_error: 0.0143 - mean_squared_error: 4.2405e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 201us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30480.5527 - mean_absolute_error: 0.0211 - mean_squared_error: 0.0037 - val_loss: 8.8209e-04 - val_mean_absolute_percentage_error: 64.8195 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 8.8209e-04\n",
      "Epoch 294/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 7.9652e-04 - mean_absolute_percentage_error: 34.9511 - mean_absolute_error: 0.0184 - mean_squared_error: 7.9652e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 182us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29915.7227 - mean_absolute_error: 0.0210 - mean_squared_error: 0.0037 - val_loss: 8.6997e-04 - val_mean_absolute_percentage_error: 63.9887 - val_mean_absolute_error: 0.0195 - val_mean_squared_error: 8.6997e-04\n",
      "Epoch 295/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.5839e-04 - mean_absolute_percentage_error: 30.5959 - mean_absolute_error: 0.0187 - mean_squared_error: 6.5839e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 182us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29915.8203 - mean_absolute_error: 0.0209 - mean_squared_error: 0.0037 - val_loss: 8.6380e-04 - val_mean_absolute_percentage_error: 64.9460 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.6380e-04\n",
      "Epoch 296/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0258 - mean_absolute_percentage_error: 26.2889 - mean_absolute_error: 0.0496 - mean_squared_error: 0.0258",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30723.7676 - mean_absolute_error: 0.0212 - mean_squared_error: 0.0037 - val_loss: 8.5208e-04 - val_mean_absolute_percentage_error: 64.3468 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 8.5208e-04\n",
      "Epoch 297/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.2297e-04 - mean_absolute_percentage_error: 274011.2812 - mean_absolute_error: 0.0152 - mean_squared_error: 5.2297e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 196us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30374.0449 - mean_absolute_error: 0.0209 - mean_squared_error: 0.0037 - val_loss: 8.4493e-04 - val_mean_absolute_percentage_error: 63.4080 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 8.4493e-04\n",
      "Epoch 298/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.2490e-04 - mean_absolute_percentage_error: 39.0732 - mean_absolute_error: 0.0128 - mean_squared_error: 3.2490e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29539.6133 - mean_absolute_error: 0.0207 - mean_squared_error: 0.0037 - val_loss: 8.4518e-04 - val_mean_absolute_percentage_error: 62.4373 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.4518e-04\n",
      "Epoch 299/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 9.4325e-04 - mean_absolute_percentage_error: 261698.7656 - mean_absolute_error: 0.0215 - mean_squared_error: 9.4325e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 196us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29008.5703 - mean_absolute_error: 0.0207 - mean_squared_error: 0.0037 - val_loss: 8.4917e-04 - val_mean_absolute_percentage_error: 62.5766 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.4917e-04\n",
      "Epoch 300/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 4.9723e-04 - mean_absolute_percentage_error: 44.7067 - mean_absolute_error: 0.0145 - mean_squared_error: 4.9723e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29768.6895 - mean_absolute_error: 0.0209 - mean_squared_error: 0.0037 - val_loss: 8.6481e-04 - val_mean_absolute_percentage_error: 64.0994 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.6481e-04\n",
      "Epoch 301/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.8554e-04 - mean_absolute_percentage_error: 30.9077 - mean_absolute_error: 0.0123 - mean_squared_error: 2.8554e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 228us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29539.7676 - mean_absolute_error: 0.0209 - mean_squared_error: 0.0037 - val_loss: 8.5926e-04 - val_mean_absolute_percentage_error: 63.4746 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.5926e-04\n",
      "Epoch 302/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0011 - mean_absolute_percentage_error: 22.1180 - mean_absolute_error: 0.0220 - mean_squared_error: 0.0011",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 186us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29213.6602 - mean_absolute_error: 0.0208 - mean_squared_error: 0.0037 - val_loss: 8.5442e-04 - val_mean_absolute_percentage_error: 63.2991 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 8.5442e-04\n",
      "Epoch 303/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0245 - mean_absolute_percentage_error: 28.0561 - mean_absolute_error: 0.0404 - mean_squared_error: 0.0245",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30090.7188 - mean_absolute_error: 0.0210 - mean_squared_error: 0.0037 - val_loss: 8.6497e-04 - val_mean_absolute_percentage_error: 64.5764 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.6497e-04\n",
      "Epoch 304/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 6.4769e-04 - mean_absolute_percentage_error: 24.2607 - mean_absolute_error: 0.0164 - mean_squared_error: 6.4769e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 190us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30043.0371 - mean_absolute_error: 0.0211 - mean_squared_error: 0.0037 - val_loss: 8.5040e-04 - val_mean_absolute_percentage_error: 63.9466 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 8.5040e-04\n",
      "Epoch 305/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.0270e-04 - mean_absolute_percentage_error: 21.7053 - mean_absolute_error: 0.0167 - mean_squared_error: 6.0270e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 212us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29116.0137 - mean_absolute_error: 0.0207 - mean_squared_error: 0.0037 - val_loss: 8.3708e-04 - val_mean_absolute_percentage_error: 62.8219 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 8.3708e-04\n",
      "Epoch 306/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.5677e-04 - mean_absolute_percentage_error: 63.3693 - mean_absolute_error: 0.0178 - mean_squared_error: 6.5677e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 226us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28472.0820 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0037 - val_loss: 8.3081e-04 - val_mean_absolute_percentage_error: 61.7330 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 8.3081e-04\n",
      "Epoch 307/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0011 - mean_absolute_percentage_error: 40.8702 - mean_absolute_error: 0.0249 - mean_squared_error: 0.0011",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 224us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28415.8438 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0037 - val_loss: 8.4227e-04 - val_mean_absolute_percentage_error: 61.8702 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 8.4227e-04\n",
      "Epoch 308/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.6861e-04 - mean_absolute_percentage_error: 33.2015 - mean_absolute_error: 0.0139 - mean_squared_error: 3.6861e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 191us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28451.5000 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0037 - val_loss: 8.6703e-04 - val_mean_absolute_percentage_error: 63.3263 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.6703e-04\n",
      "Epoch 309/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0247 - mean_absolute_percentage_error: 261469.8438 - mean_absolute_error: 0.0433 - mean_squared_error: 0.0247",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 193us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28984.0449 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0037 - val_loss: 8.5659e-04 - val_mean_absolute_percentage_error: 62.8133 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 8.5659e-04\n",
      "Epoch 310/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.1593e-04 - mean_absolute_percentage_error: 22.6322 - mean_absolute_error: 0.0162 - mean_squared_error: 6.1593e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28901.0488 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0037 - val_loss: 8.5259e-04 - val_mean_absolute_percentage_error: 62.8078 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 8.5259e-04\n",
      "Epoch 311/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 5.2560e-04 - mean_absolute_percentage_error: 22.3717 - mean_absolute_error: 0.0163 - mean_squared_error: 5.2560e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28601.0742 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0037 - val_loss: 8.4813e-04 - val_mean_absolute_percentage_error: 62.6653 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 8.4813e-04\n",
      "Epoch 312/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.9726e-04 - mean_absolute_percentage_error: 73.9334 - mean_absolute_error: 0.0181 - mean_squared_error: 6.9726e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28959.1562 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0037 - val_loss: 8.5000e-04 - val_mean_absolute_percentage_error: 62.8854 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 8.5000e-04\n",
      "Epoch 313/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.8497e-04 - mean_absolute_percentage_error: 82.3644 - mean_absolute_error: 0.0142 - mean_squared_error: 3.8497e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 185us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28659.0957 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0037 - val_loss: 8.5355e-04 - val_mean_absolute_percentage_error: 62.4505 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 8.5355e-04\n",
      "Epoch 314/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 5.0107e-04 - mean_absolute_percentage_error: 41.7210 - mean_absolute_error: 0.0163 - mean_squared_error: 5.0107e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28462.6035 - mean_absolute_error: 0.0203 - mean_squared_error: 0.0037 - val_loss: 8.5570e-04 - val_mean_absolute_percentage_error: 62.8187 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 8.5570e-04\n",
      "Epoch 315/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.2035e-04 - mean_absolute_percentage_error: 62.9820 - mean_absolute_error: 0.0168 - mean_squared_error: 5.2035e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29355.1172 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 8.8105e-04 - val_mean_absolute_percentage_error: 64.2989 - val_mean_absolute_error: 0.0197 - val_mean_squared_error: 8.8105e-04\n",
      "Epoch 316/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.3366e-04 - mean_absolute_percentage_error: 56.3359 - mean_absolute_error: 0.0144 - mean_squared_error: 3.3366e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29437.8750 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0037 - val_loss: 8.7816e-04 - val_mean_absolute_percentage_error: 64.1838 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 8.7816e-04\n",
      "Epoch 317/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.6926e-04 - mean_absolute_percentage_error: 19.8843 - mean_absolute_error: 0.0099 - mean_squared_error: 2.6926e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29590.5391 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 8.7220e-04 - val_mean_absolute_percentage_error: 64.1189 - val_mean_absolute_error: 0.0195 - val_mean_squared_error: 8.7220e-04\n",
      "Epoch 318/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.1870e-04 - mean_absolute_percentage_error: 17.9604 - mean_absolute_error: 0.0135 - mean_squared_error: 3.1870e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 182us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29714.7988 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0037 - val_loss: 8.6859e-04 - val_mean_absolute_percentage_error: 63.8449 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.6859e-04\n",
      "Epoch 319/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.0539e-04 - mean_absolute_percentage_error: 35.0059 - mean_absolute_error: 0.0131 - mean_squared_error: 3.0539e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28492.7051 - mean_absolute_error: 0.0203 - mean_squared_error: 0.0037 - val_loss: 8.1090e-04 - val_mean_absolute_percentage_error: 60.9136 - val_mean_absolute_error: 0.0187 - val_mean_squared_error: 8.1090e-04\n",
      "Epoch 320/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.0653e-04 - mean_absolute_percentage_error: 254438.0938 - mean_absolute_error: 0.0183 - mean_squared_error: 6.0653e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 192us/sample - loss: 0.0037 - mean_absolute_percentage_error: 28205.0957 - mean_absolute_error: 0.0202 - mean_squared_error: 0.0037 - val_loss: 8.0634e-04 - val_mean_absolute_percentage_error: 60.9330 - val_mean_absolute_error: 0.0187 - val_mean_squared_error: 8.0634e-04\n",
      "Epoch 321/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 4.5297e-04 - mean_absolute_percentage_error: 31.1736 - mean_absolute_error: 0.0164 - mean_squared_error: 4.5297e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 189us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28372.8477 - mean_absolute_error: 0.0203 - mean_squared_error: 0.0036 - val_loss: 8.2389e-04 - val_mean_absolute_percentage_error: 61.9626 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 8.2389e-04\n",
      "Epoch 322/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 9.7006e-04 - mean_absolute_percentage_error: 39.2531 - mean_absolute_error: 0.0203 - mean_squared_error: 9.7006e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 180us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29875.8828 - mean_absolute_error: 0.0207 - mean_squared_error: 0.0037 - val_loss: 8.5979e-04 - val_mean_absolute_percentage_error: 64.1399 - val_mean_absolute_error: 0.0194 - val_mean_squared_error: 8.5979e-04\n",
      "Epoch 323/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.2586e-04 - mean_absolute_percentage_error: 25.1423 - mean_absolute_error: 0.0128 - mean_squared_error: 3.2586e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29872.5820 - mean_absolute_error: 0.0207 - mean_squared_error: 0.0036 - val_loss: 8.5786e-04 - val_mean_absolute_percentage_error: 63.3797 - val_mean_absolute_error: 0.0194 - val_mean_squared_error: 8.5786e-04\n",
      "Epoch 324/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.1632e-04 - mean_absolute_percentage_error: 63.8646 - mean_absolute_error: 0.0119 - mean_squared_error: 3.1632e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29337.1582 - mean_absolute_error: 0.0208 - mean_squared_error: 0.0036 - val_loss: 8.7637e-04 - val_mean_absolute_percentage_error: 63.1442 - val_mean_absolute_error: 0.0197 - val_mean_squared_error: 8.7637e-04\n",
      "Epoch 325/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.2890e-04 - mean_absolute_percentage_error: 28.7905 - mean_absolute_error: 0.0161 - mean_squared_error: 5.2890e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28818.0918 - mean_absolute_error: 0.0209 - mean_squared_error: 0.0036 - val_loss: 8.6351e-04 - val_mean_absolute_percentage_error: 62.6084 - val_mean_absolute_error: 0.0194 - val_mean_squared_error: 8.6351e-04\n",
      "Epoch 326/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.0805e-04 - mean_absolute_percentage_error: 31.2977 - mean_absolute_error: 0.0148 - mean_squared_error: 4.0805e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 180us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28786.5508 - mean_absolute_error: 0.0209 - mean_squared_error: 0.0036 - val_loss: 8.6819e-04 - val_mean_absolute_percentage_error: 63.0438 - val_mean_absolute_error: 0.0194 - val_mean_squared_error: 8.6819e-04\n",
      "Epoch 327/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.1773e-04 - mean_absolute_percentage_error: 59.8779 - mean_absolute_error: 0.0190 - mean_squared_error: 6.1773e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 201us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28945.5312 - mean_absolute_error: 0.0208 - mean_squared_error: 0.0036 - val_loss: 8.6108e-04 - val_mean_absolute_percentage_error: 63.0284 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.6108e-04\n",
      "Epoch 328/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 4.6138e-04 - mean_absolute_percentage_error: 29.9746 - mean_absolute_error: 0.0155 - mean_squared_error: 4.6138e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28377.7520 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0036 - val_loss: 8.4208e-04 - val_mean_absolute_percentage_error: 61.6518 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 8.4208e-04\n",
      "Epoch 329/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.6205e-04 - mean_absolute_percentage_error: 40.5968 - mean_absolute_error: 0.0165 - mean_squared_error: 5.6205e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 190us/sample - loss: 0.0036 - mean_absolute_percentage_error: 27855.9941 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 8.1837e-04 - val_mean_absolute_percentage_error: 61.1539 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 8.1837e-04\n",
      "Epoch 330/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0029 - mean_absolute_percentage_error: 28.5811 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0029",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28282.3066 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 8.1919e-04 - val_mean_absolute_percentage_error: 61.4683 - val_mean_absolute_error: 0.0187 - val_mean_squared_error: 8.1919e-04\n",
      "Epoch 331/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.8833e-04 - mean_absolute_percentage_error: 255009.6719 - mean_absolute_error: 0.0112 - mean_squared_error: 2.8833e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 196us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28267.3672 - mean_absolute_error: 0.0203 - mean_squared_error: 0.0036 - val_loss: 8.0716e-04 - val_mean_absolute_percentage_error: 60.4251 - val_mean_absolute_error: 0.0186 - val_mean_squared_error: 8.0716e-04\n",
      "Epoch 332/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.9749e-04 - mean_absolute_percentage_error: 35.9610 - mean_absolute_error: 0.0176 - mean_squared_error: 6.9749e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 208us/sample - loss: 0.0036 - mean_absolute_percentage_error: 27515.3633 - mean_absolute_error: 0.0201 - mean_squared_error: 0.0036 - val_loss: 8.1003e-04 - val_mean_absolute_percentage_error: 60.4017 - val_mean_absolute_error: 0.0187 - val_mean_squared_error: 8.1003e-04\n",
      "Epoch 333/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.0031e-04 - mean_absolute_percentage_error: 33.9376 - mean_absolute_error: 0.0166 - mean_squared_error: 4.0031e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0036 - mean_absolute_percentage_error: 27175.3633 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0036 - val_loss: 7.9012e-04 - val_mean_absolute_percentage_error: 59.3433 - val_mean_absolute_error: 0.0183 - val_mean_squared_error: 7.9012e-04\n",
      "Epoch 334/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0019 - mean_absolute_percentage_error: 244520.1719 - mean_absolute_error: 0.0246 - mean_squared_error: 0.0019",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 215us/sample - loss: 0.0036 - mean_absolute_percentage_error: 27105.8418 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0036 - val_loss: 8.0274e-04 - val_mean_absolute_percentage_error: 60.6801 - val_mean_absolute_error: 0.0184 - val_mean_squared_error: 8.0274e-04\n",
      "Epoch 335/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 7.2234e-04 - mean_absolute_percentage_error: 37.7595 - mean_absolute_error: 0.0155 - mean_squared_error: 7.2234e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 249us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29285.7539 - mean_absolute_error: 0.0201 - mean_squared_error: 0.0036 - val_loss: 9.0188e-04 - val_mean_absolute_percentage_error: 65.9298 - val_mean_absolute_error: 0.0203 - val_mean_squared_error: 9.0188e-04\n",
      "Epoch 336/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 9.7465e-04 - mean_absolute_percentage_error: 39.5243 - mean_absolute_error: 0.0211 - mean_squared_error: 9.7465e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 222us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30457.8555 - mean_absolute_error: 0.0208 - mean_squared_error: 0.0037 - val_loss: 9.4613e-04 - val_mean_absolute_percentage_error: 67.2041 - val_mean_absolute_error: 0.0210 - val_mean_squared_error: 9.4613e-04\n",
      "Epoch 337/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.4577e-04 - mean_absolute_percentage_error: 38.7762 - mean_absolute_error: 0.0154 - mean_squared_error: 6.4577e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 246us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30523.4023 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0036 - val_loss: 8.9481e-04 - val_mean_absolute_percentage_error: 64.5638 - val_mean_absolute_error: 0.0203 - val_mean_squared_error: 8.9481e-04\n",
      "Epoch 338/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.2688e-04 - mean_absolute_percentage_error: 29.1460 - mean_absolute_error: 0.0178 - mean_squared_error: 6.2688e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 246us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29566.5391 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0036 - val_loss: 8.7427e-04 - val_mean_absolute_percentage_error: 64.0115 - val_mean_absolute_error: 0.0200 - val_mean_squared_error: 8.7427e-04\n",
      "Epoch 339/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.9093e-04 - mean_absolute_percentage_error: 28.4817 - mean_absolute_error: 0.0162 - mean_squared_error: 4.9093e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 241us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29423.0586 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0036 - val_loss: 8.5072e-04 - val_mean_absolute_percentage_error: 63.3229 - val_mean_absolute_error: 0.0195 - val_mean_squared_error: 8.5072e-04\n",
      "Epoch 340/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0033 - mean_absolute_percentage_error: 61.1414 - mean_absolute_error: 0.0275 - mean_squared_error: 0.0033",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 245us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28872.7578 - mean_absolute_error: 0.0203 - mean_squared_error: 0.0036 - val_loss: 8.3446e-04 - val_mean_absolute_percentage_error: 61.7904 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 8.3446e-04\n",
      "Epoch 341/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0244 - mean_absolute_percentage_error: 42.7107 - mean_absolute_error: 0.0377 - mean_squared_error: 0.0244",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 265us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28555.5605 - mean_absolute_error: 0.0202 - mean_squared_error: 0.0036 - val_loss: 8.3400e-04 - val_mean_absolute_percentage_error: 61.9551 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 8.3400e-04\n",
      "Epoch 342/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 8.4313e-04 - mean_absolute_percentage_error: 38.4211 - mean_absolute_error: 0.0173 - mean_squared_error: 8.4313e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 241us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28390.8867 - mean_absolute_error: 0.0201 - mean_squared_error: 0.0036 - val_loss: 8.2756e-04 - val_mean_absolute_percentage_error: 61.9962 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 8.2756e-04\n",
      "Epoch 343/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.9237e-04 - mean_absolute_percentage_error: 33.6080 - mean_absolute_error: 0.0134 - mean_squared_error: 2.9237e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 250us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29097.3262 - mean_absolute_error: 0.0202 - mean_squared_error: 0.0036 - val_loss: 8.2674e-04 - val_mean_absolute_percentage_error: 62.8127 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 8.2674e-04\n",
      "Epoch 344/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.8750e-04 - mean_absolute_percentage_error: 39.5570 - mean_absolute_error: 0.0165 - mean_squared_error: 5.8750e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 234us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28289.1348 - mean_absolute_error: 0.0201 - mean_squared_error: 0.0036 - val_loss: 7.3730e-04 - val_mean_absolute_percentage_error: 58.6646 - val_mean_absolute_error: 0.0182 - val_mean_squared_error: 7.3730e-04\n",
      "Epoch 345/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.7008e-04 - mean_absolute_percentage_error: 40.8833 - mean_absolute_error: 0.0168 - mean_squared_error: 6.7008e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 226us/sample - loss: 0.0037 - mean_absolute_percentage_error: 26827.5605 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0037 - val_loss: 6.6324e-04 - val_mean_absolute_percentage_error: 53.8657 - val_mean_absolute_error: 0.0176 - val_mean_squared_error: 6.6324e-04\n",
      "Epoch 346/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 8.0289e-04 - mean_absolute_percentage_error: 57.4449 - mean_absolute_error: 0.0211 - mean_squared_error: 8.0289e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 259us/sample - loss: 0.0037 - mean_absolute_percentage_error: 27300.2461 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0037 - val_loss: 6.8295e-04 - val_mean_absolute_percentage_error: 57.7250 - val_mean_absolute_error: 0.0180 - val_mean_squared_error: 6.8295e-04\n",
      "Epoch 347/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0248 - mean_absolute_percentage_error: 24.9805 - mean_absolute_error: 0.0413 - mean_squared_error: 0.0248",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 260us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29058.8613 - mean_absolute_error: 0.0202 - mean_squared_error: 0.0037 - val_loss: 7.1133e-04 - val_mean_absolute_percentage_error: 59.7280 - val_mean_absolute_error: 0.0184 - val_mean_squared_error: 7.1133e-04\n",
      "Epoch 348/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 1.9301e-04 - mean_absolute_percentage_error: 22.5544 - mean_absolute_error: 0.0112 - mean_squared_error: 1.9301e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 234us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29807.3867 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0037 - val_loss: 7.0992e-04 - val_mean_absolute_percentage_error: 61.5707 - val_mean_absolute_error: 0.0187 - val_mean_squared_error: 7.0992e-04\n",
      "Epoch 349/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0276 - mean_absolute_percentage_error: 34.2476 - mean_absolute_error: 0.0505 - mean_squared_error: 0.0276",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 243us/sample - loss: 0.0037 - mean_absolute_percentage_error: 30368.5332 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0037 - val_loss: 7.1890e-04 - val_mean_absolute_percentage_error: 61.6044 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.1890e-04\n",
      "Epoch 350/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.1177e-04 - mean_absolute_percentage_error: 69.8701 - mean_absolute_error: 0.0152 - mean_squared_error: 4.1177e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 238us/sample - loss: 0.0037 - mean_absolute_percentage_error: 29513.3105 - mean_absolute_error: 0.0194 - mean_squared_error: 0.0037 - val_loss: 7.2308e-04 - val_mean_absolute_percentage_error: 60.9869 - val_mean_absolute_error: 0.0187 - val_mean_squared_error: 7.2308e-04\n",
      "Epoch 351/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0247 - mean_absolute_percentage_error: 25.0236 - mean_absolute_error: 0.0420 - mean_squared_error: 0.0247",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 239us/sample - loss: 0.0037 - mean_absolute_percentage_error: 31146.3184 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0037 - val_loss: 7.4263e-04 - val_mean_absolute_percentage_error: 63.5282 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.4263e-04\n",
      "Epoch 352/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0246 - mean_absolute_percentage_error: 23.3380 - mean_absolute_error: 0.0411 - mean_squared_error: 0.0246",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 246us/sample - loss: 0.0036 - mean_absolute_percentage_error: 31333.2051 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0036 - val_loss: 7.5761e-04 - val_mean_absolute_percentage_error: 63.7127 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.5761e-04\n",
      "Epoch 353/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.6747e-04 - mean_absolute_percentage_error: 62.9061 - mean_absolute_error: 0.0146 - mean_squared_error: 4.6747e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 238us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30673.3711 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0036 - val_loss: 7.6584e-04 - val_mean_absolute_percentage_error: 63.0440 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.6584e-04\n",
      "Epoch 354/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0261 - mean_absolute_percentage_error: 62.2049 - mean_absolute_error: 0.0520 - mean_squared_error: 0.0261",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 224us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30612.4609 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0036 - val_loss: 7.9166e-04 - val_mean_absolute_percentage_error: 63.8135 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.9166e-04\n",
      "Epoch 355/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.7897e-04 - mean_absolute_percentage_error: 35.2412 - mean_absolute_error: 0.0132 - mean_squared_error: 2.7897e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 241us/sample - loss: 0.0036 - mean_absolute_percentage_error: 31094.6738 - mean_absolute_error: 0.0201 - mean_squared_error: 0.0036 - val_loss: 8.4277e-04 - val_mean_absolute_percentage_error: 65.6212 - val_mean_absolute_error: 0.0198 - val_mean_squared_error: 8.4277e-04\n",
      "Epoch 356/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.1962e-04 - mean_absolute_percentage_error: 32.3759 - mean_absolute_error: 0.0144 - mean_squared_error: 3.1962e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 243us/sample - loss: 0.0036 - mean_absolute_percentage_error: 31469.7754 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 8.5731e-04 - val_mean_absolute_percentage_error: 66.5175 - val_mean_absolute_error: 0.0199 - val_mean_squared_error: 8.5731e-04\n",
      "Epoch 357/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.1752e-04 - mean_absolute_percentage_error: 26.7217 - mean_absolute_error: 0.0134 - mean_squared_error: 3.1752e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 248us/sample - loss: 0.0036 - mean_absolute_percentage_error: 31363.6055 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0036 - val_loss: 8.4835e-04 - val_mean_absolute_percentage_error: 65.2607 - val_mean_absolute_error: 0.0198 - val_mean_squared_error: 8.4835e-04\n",
      "Epoch 358/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.9687e-04 - mean_absolute_percentage_error: 277345.1250 - mean_absolute_error: 0.0133 - mean_squared_error: 2.9687e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 238us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30744.9453 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 8.3562e-04 - val_mean_absolute_percentage_error: 64.8230 - val_mean_absolute_error: 0.0195 - val_mean_squared_error: 8.3562e-04\n",
      "Epoch 359/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.3638e-04 - mean_absolute_percentage_error: 275583.0938 - mean_absolute_error: 0.0152 - mean_squared_error: 4.3638e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 227us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30548.6719 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 7.9832e-04 - val_mean_absolute_percentage_error: 63.3584 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.9832e-04\n",
      "Epoch 360/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0029 - mean_absolute_percentage_error: 48.5495 - mean_absolute_error: 0.0218 - mean_squared_error: 0.0029",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 250us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28401.8516 - mean_absolute_error: 0.0202 - mean_squared_error: 0.0036 - val_loss: 6.8686e-04 - val_mean_absolute_percentage_error: 56.8029 - val_mean_absolute_error: 0.0180 - val_mean_squared_error: 6.8686e-04\n",
      "Epoch 361/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0016 - mean_absolute_percentage_error: 24.5512 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0016",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 245us/sample - loss: 0.0037 - mean_absolute_percentage_error: 27439.5078 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0037 - val_loss: 6.7144e-04 - val_mean_absolute_percentage_error: 57.9133 - val_mean_absolute_error: 0.0177 - val_mean_squared_error: 6.7144e-04\n",
      "Epoch 362/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 7.4757e-04 - mean_absolute_percentage_error: 23.1765 - mean_absolute_error: 0.0190 - mean_squared_error: 7.4757e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 252us/sample - loss: 0.0037 - mean_absolute_percentage_error: 31952.5469 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0037 - val_loss: 7.8015e-04 - val_mean_absolute_percentage_error: 66.0030 - val_mean_absolute_error: 0.0198 - val_mean_squared_error: 7.8015e-04\n",
      "Epoch 363/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.2131e-04 - mean_absolute_percentage_error: 28.6755 - mean_absolute_error: 0.0126 - mean_squared_error: 3.2131e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 239us/sample - loss: 0.0037 - mean_absolute_percentage_error: 32692.5430 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0037 - val_loss: 8.0329e-04 - val_mean_absolute_percentage_error: 65.8732 - val_mean_absolute_error: 0.0201 - val_mean_squared_error: 8.0329e-04\n",
      "Epoch 364/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.7980e-04 - mean_absolute_percentage_error: 35.7620 - mean_absolute_error: 0.0151 - mean_squared_error: 4.7980e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 244us/sample - loss: 0.0037 - mean_absolute_percentage_error: 31403.0840 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0037 - val_loss: 7.7243e-04 - val_mean_absolute_percentage_error: 63.5191 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 7.7243e-04\n",
      "Epoch 365/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 1.7521e-04 - mean_absolute_percentage_error: 32.2385 - mean_absolute_error: 0.0102 - mean_squared_error: 1.7521e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 238us/sample - loss: 0.0036 - mean_absolute_percentage_error: 31271.1836 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0036 - val_loss: 7.5394e-04 - val_mean_absolute_percentage_error: 62.9435 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 7.5394e-04\n",
      "Epoch 366/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0248 - mean_absolute_percentage_error: 26.5665 - mean_absolute_error: 0.0451 - mean_squared_error: 0.0248",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30615.7188 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0036 - val_loss: 6.9137e-04 - val_mean_absolute_percentage_error: 60.0770 - val_mean_absolute_error: 0.0180 - val_mean_squared_error: 6.9137e-04\n",
      "Epoch 367/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0245 - mean_absolute_percentage_error: 270531.9375 - mean_absolute_error: 0.0418 - mean_squared_error: 0.0245",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 193us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29984.8828 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0036 - val_loss: 6.7577e-04 - val_mean_absolute_percentage_error: 60.3779 - val_mean_absolute_error: 0.0177 - val_mean_squared_error: 6.7577e-04\n",
      "Epoch 368/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.2130e-04 - mean_absolute_percentage_error: 20.8305 - mean_absolute_error: 0.0114 - mean_squared_error: 2.2130e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 189us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30988.5430 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0036 - val_loss: 6.9147e-04 - val_mean_absolute_percentage_error: 62.2068 - val_mean_absolute_error: 0.0179 - val_mean_squared_error: 6.9147e-04\n",
      "Epoch 369/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.5612e-04 - mean_absolute_percentage_error: 41.9726 - mean_absolute_error: 0.0134 - mean_squared_error: 3.5612e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 188us/sample - loss: 0.0036 - mean_absolute_percentage_error: 31038.3359 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0036 - val_loss: 7.0565e-04 - val_mean_absolute_percentage_error: 62.3919 - val_mean_absolute_error: 0.0181 - val_mean_squared_error: 7.0565e-04\n",
      "Epoch 370/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0035 - mean_absolute_percentage_error: 40.8853 - mean_absolute_error: 0.0298 - mean_squared_error: 0.0035",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30846.6719 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0036 - val_loss: 7.3718e-04 - val_mean_absolute_percentage_error: 63.4557 - val_mean_absolute_error: 0.0185 - val_mean_squared_error: 7.3718e-04\n",
      "Epoch 371/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0016 - mean_absolute_percentage_error: 29.1678 - mean_absolute_error: 0.0187 - mean_squared_error: 0.0016",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0036 - mean_absolute_percentage_error: 31187.8691 - mean_absolute_error: 0.0202 - mean_squared_error: 0.0036 - val_loss: 7.4937e-04 - val_mean_absolute_percentage_error: 64.4533 - val_mean_absolute_error: 0.0187 - val_mean_squared_error: 7.4937e-04\n",
      "Epoch 372/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 9.0485e-04 - mean_absolute_percentage_error: 99.5991 - mean_absolute_error: 0.0195 - mean_squared_error: 9.0485e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 196us/sample - loss: 0.0036 - mean_absolute_percentage_error: 31293.6133 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 7.6665e-04 - val_mean_absolute_percentage_error: 64.5621 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.6665e-04\n",
      "Epoch 373/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0018 - mean_absolute_percentage_error: 38.3115 - mean_absolute_error: 0.0239 - mean_squared_error: 0.0018",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0036 - mean_absolute_percentage_error: 31191.4043 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0036 - val_loss: 7.8040e-04 - val_mean_absolute_percentage_error: 64.2256 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.8040e-04\n",
      "Epoch 374/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.3747e-04 - mean_absolute_percentage_error: 36.1046 - mean_absolute_error: 0.0117 - mean_squared_error: 2.3747e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 183us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30413.4121 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0036 - val_loss: 7.7480e-04 - val_mean_absolute_percentage_error: 62.8093 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.7480e-04\n",
      "Epoch 375/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 4.4958e-04 - mean_absolute_percentage_error: 29.5214 - mean_absolute_error: 0.0163 - mean_squared_error: 4.4958e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 196us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29701.4805 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 7.8115e-04 - val_mean_absolute_percentage_error: 62.5101 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.8115e-04\n",
      "Epoch 376/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0244 - mean_absolute_percentage_error: 267214.6875 - mean_absolute_error: 0.0432 - mean_squared_error: 0.0244",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29620.8066 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0036 - val_loss: 7.8546e-04 - val_mean_absolute_percentage_error: 62.8476 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.8546e-04\n",
      "Epoch 377/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0268 - mean_absolute_percentage_error: 38.2379 - mean_absolute_error: 0.0525 - mean_squared_error: 0.0268",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30206.2598 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0036 - val_loss: 7.8536e-04 - val_mean_absolute_percentage_error: 63.4312 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.8536e-04\n",
      "Epoch 378/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.0941e-04 - mean_absolute_percentage_error: 273648.5000 - mean_absolute_error: 0.0105 - mean_squared_error: 2.0941e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 188us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30334.7852 - mean_absolute_error: 0.0203 - mean_squared_error: 0.0036 - val_loss: 7.6143e-04 - val_mean_absolute_percentage_error: 61.7866 - val_mean_absolute_error: 0.0185 - val_mean_squared_error: 7.6143e-04\n",
      "Epoch 379/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0044 - mean_absolute_percentage_error: 30.7219 - mean_absolute_error: 0.0325 - mean_squared_error: 0.0044",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29004.0215 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0036 - val_loss: 7.7059e-04 - val_mean_absolute_percentage_error: 61.9002 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.7059e-04\n",
      "Epoch 380/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 8.8895e-04 - mean_absolute_percentage_error: 35.0079 - mean_absolute_error: 0.0207 - mean_squared_error: 8.8895e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29766.1562 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0036 - val_loss: 7.9942e-04 - val_mean_absolute_percentage_error: 63.4071 - val_mean_absolute_error: 0.0195 - val_mean_squared_error: 7.9942e-04\n",
      "Epoch 381/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.4501e-04 - mean_absolute_percentage_error: 31.2126 - mean_absolute_error: 0.0143 - mean_squared_error: 3.4501e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29662.2871 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0036 - val_loss: 8.0749e-04 - val_mean_absolute_percentage_error: 63.0431 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 8.0749e-04\n",
      "Epoch 382/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 3.4216e-04 - mean_absolute_percentage_error: 30.5549 - mean_absolute_error: 0.0138 - mean_squared_error: 3.4216e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28691.1660 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0036 - val_loss: 8.0186e-04 - val_mean_absolute_percentage_error: 61.6684 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 8.0186e-04\n",
      "Epoch 383/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 4.6848e-04 - mean_absolute_percentage_error: 28.8409 - mean_absolute_error: 0.0164 - mean_squared_error: 4.6848e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29891.7305 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0036 - val_loss: 9.0707e-04 - val_mean_absolute_percentage_error: 66.6684 - val_mean_absolute_error: 0.0213 - val_mean_squared_error: 9.0707e-04\n",
      "Epoch 384/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.0498e-04 - mean_absolute_percentage_error: 279961.6250 - mean_absolute_error: 0.0118 - mean_squared_error: 2.0498e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0036 - mean_absolute_percentage_error: 31037.3633 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0036 - val_loss: 0.0010 - val_mean_absolute_percentage_error: 71.2259 - val_mean_absolute_error: 0.0226 - val_mean_squared_error: 0.0010\n",
      "Epoch 385/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 4.6918e-04 - mean_absolute_percentage_error: 46.9969 - mean_absolute_error: 0.0162 - mean_squared_error: 4.6918e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0036 - mean_absolute_percentage_error: 32290.6328 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 8.4375e-04 - val_mean_absolute_percentage_error: 64.7489 - val_mean_absolute_error: 0.0204 - val_mean_squared_error: 8.4375e-04\n",
      "Epoch 386/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.5781e-04 - mean_absolute_percentage_error: 275190.3438 - mean_absolute_error: 0.0130 - mean_squared_error: 5.5781e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 190us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30505.3730 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0036 - val_loss: 7.9753e-04 - val_mean_absolute_percentage_error: 62.9941 - val_mean_absolute_error: 0.0197 - val_mean_squared_error: 7.9753e-04\n",
      "Epoch 387/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0242 - mean_absolute_percentage_error: 26.1052 - mean_absolute_error: 0.0382 - mean_squared_error: 0.0242",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0036 - mean_absolute_percentage_error: 30107.2734 - mean_absolute_error: 0.0201 - mean_squared_error: 0.0036 - val_loss: 7.9302e-04 - val_mean_absolute_percentage_error: 63.1938 - val_mean_absolute_error: 0.0194 - val_mean_squared_error: 7.9302e-04\n",
      "Epoch 388/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.3100e-04 - mean_absolute_percentage_error: 23.2649 - mean_absolute_error: 0.0112 - mean_squared_error: 2.3100e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0036 - mean_absolute_percentage_error: 29110.5703 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0036 - val_loss: 7.8107e-04 - val_mean_absolute_percentage_error: 61.4824 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 7.8107e-04\n",
      "Epoch 389/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.8142e-04 - mean_absolute_percentage_error: 27.3286 - mean_absolute_error: 0.0180 - mean_squared_error: 5.8142e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28617.9297 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0036 - val_loss: 7.8265e-04 - val_mean_absolute_percentage_error: 61.6279 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.8265e-04\n",
      "Epoch 390/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.3348e-04 - mean_absolute_percentage_error: 25.9706 - mean_absolute_error: 0.0152 - mean_squared_error: 4.3348e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28367.3965 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0036 - val_loss: 8.0386e-04 - val_mean_absolute_percentage_error: 61.5498 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.0386e-04\n",
      "Epoch 391/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0034 - mean_absolute_percentage_error: 35.9859 - mean_absolute_error: 0.0254 - mean_squared_error: 0.0034",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28308.0840 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0036 - val_loss: 8.2788e-04 - val_mean_absolute_percentage_error: 62.1969 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 8.2788e-04\n",
      "Epoch 392/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.4026e-04 - mean_absolute_percentage_error: 21.3836 - mean_absolute_error: 0.0186 - mean_squared_error: 6.4026e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28567.4922 - mean_absolute_error: 0.0204 - mean_squared_error: 0.0036 - val_loss: 8.3296e-04 - val_mean_absolute_percentage_error: 63.7147 - val_mean_absolute_error: 0.0197 - val_mean_squared_error: 8.3296e-04\n",
      "Epoch 393/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0033 - mean_absolute_percentage_error: 35.7831 - mean_absolute_error: 0.0290 - mean_squared_error: 0.0033",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 201us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28646.7285 - mean_absolute_error: 0.0202 - mean_squared_error: 0.0036 - val_loss: 8.0294e-04 - val_mean_absolute_percentage_error: 62.1329 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 8.0294e-04\n",
      "Epoch 394/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.3606e-04 - mean_absolute_percentage_error: 43.1953 - mean_absolute_error: 0.0157 - mean_squared_error: 5.3606e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 181us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28804.9590 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0036 - val_loss: 7.9232e-04 - val_mean_absolute_percentage_error: 62.5550 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.9232e-04\n",
      "Epoch 395/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.4074e-04 - mean_absolute_percentage_error: 259981.4844 - mean_absolute_error: 0.0118 - mean_squared_error: 2.4074e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28818.9062 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0036 - val_loss: 7.6227e-04 - val_mean_absolute_percentage_error: 61.5659 - val_mean_absolute_error: 0.0186 - val_mean_squared_error: 7.6227e-04\n",
      "Epoch 396/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.8342e-04 - mean_absolute_percentage_error: 31.4726 - mean_absolute_error: 0.0132 - mean_squared_error: 4.8342e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28983.7676 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0036 - val_loss: 7.5706e-04 - val_mean_absolute_percentage_error: 62.4226 - val_mean_absolute_error: 0.0185 - val_mean_squared_error: 7.5706e-04\n",
      "Epoch 397/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.6499e-04 - mean_absolute_percentage_error: 33.9057 - mean_absolute_error: 0.0134 - mean_squared_error: 3.6499e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28974.3418 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0035 - val_loss: 7.6170e-04 - val_mean_absolute_percentage_error: 62.4911 - val_mean_absolute_error: 0.0185 - val_mean_squared_error: 7.6170e-04\n",
      "Epoch 398/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.8722e-04 - mean_absolute_percentage_error: 28.8341 - mean_absolute_error: 0.0126 - mean_squared_error: 2.8722e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 29071.1523 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0035 - val_loss: 7.5862e-04 - val_mean_absolute_percentage_error: 62.5295 - val_mean_absolute_error: 0.0185 - val_mean_squared_error: 7.5862e-04\n",
      "Epoch 399/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 6.1900e-04 - mean_absolute_percentage_error: 57.2478 - mean_absolute_error: 0.0163 - mean_squared_error: 6.1900e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28969.8066 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0035 - val_loss: 7.6095e-04 - val_mean_absolute_percentage_error: 62.2823 - val_mean_absolute_error: 0.0185 - val_mean_squared_error: 7.6095e-04\n",
      "Epoch 400/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0031 - mean_absolute_percentage_error: 33.1134 - mean_absolute_error: 0.0240 - mean_squared_error: 0.0031",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28836.0215 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0036 - val_loss: 7.6341e-04 - val_mean_absolute_percentage_error: 61.3649 - val_mean_absolute_error: 0.0186 - val_mean_squared_error: 7.6341e-04\n",
      "Epoch 401/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0016 - mean_absolute_percentage_error: 24.1447 - mean_absolute_error: 0.0223 - mean_squared_error: 0.0016",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27867.9023 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.5248e-04 - val_mean_absolute_percentage_error: 60.8206 - val_mean_absolute_error: 0.0184 - val_mean_squared_error: 7.5248e-04\n",
      "Epoch 402/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0241 - mean_absolute_percentage_error: 29.5711 - mean_absolute_error: 0.0385 - mean_squared_error: 0.0241",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28189.5977 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0035 - val_loss: 7.5975e-04 - val_mean_absolute_percentage_error: 61.4348 - val_mean_absolute_error: 0.0185 - val_mean_squared_error: 7.5975e-04\n",
      "Epoch 403/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.0418e-04 - mean_absolute_percentage_error: 28.1409 - mean_absolute_error: 0.0154 - mean_squared_error: 4.0418e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27605.1641 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0035 - val_loss: 7.3659e-04 - val_mean_absolute_percentage_error: 59.6746 - val_mean_absolute_error: 0.0182 - val_mean_squared_error: 7.3659e-04\n",
      "Epoch 404/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0014 - mean_absolute_percentage_error: 31.7455 - mean_absolute_error: 0.0206 - mean_squared_error: 0.0014",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27088.1016 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.3163e-04 - val_mean_absolute_percentage_error: 59.5843 - val_mean_absolute_error: 0.0182 - val_mean_squared_error: 7.3163e-04\n",
      "Epoch 405/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.7643e-04 - mean_absolute_percentage_error: 28.9241 - mean_absolute_error: 0.0124 - mean_squared_error: 2.7643e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27235.4590 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.2450e-04 - val_mean_absolute_percentage_error: 61.2916 - val_mean_absolute_error: 0.0182 - val_mean_squared_error: 7.2450e-04\n",
      "Epoch 406/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.5924e-04 - mean_absolute_percentage_error: 253032.2969 - mean_absolute_error: 0.0152 - mean_squared_error: 4.5924e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28048.3730 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0035 - val_loss: 7.2758e-04 - val_mean_absolute_percentage_error: 60.8768 - val_mean_absolute_error: 0.0183 - val_mean_squared_error: 7.2758e-04\n",
      "Epoch 407/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.9869e-04 - mean_absolute_percentage_error: 28.1326 - mean_absolute_error: 0.0161 - mean_squared_error: 5.9869e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26904.2051 - mean_absolute_error: 0.0193 - mean_squared_error: 0.0035 - val_loss: 7.3849e-04 - val_mean_absolute_percentage_error: 59.1911 - val_mean_absolute_error: 0.0185 - val_mean_squared_error: 7.3849e-04\n",
      "Epoch 408/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.9484e-04 - mean_absolute_percentage_error: 241044.0156 - mean_absolute_error: 0.0158 - mean_squared_error: 4.9484e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0036 - mean_absolute_percentage_error: 26718.7695 - mean_absolute_error: 0.0193 - mean_squared_error: 0.0036 - val_loss: 7.7026e-04 - val_mean_absolute_percentage_error: 61.0047 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.7026e-04\n",
      "Epoch 409/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0012 - mean_absolute_percentage_error: 29.8952 - mean_absolute_error: 0.0159 - mean_squared_error: 0.0012",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0036 - mean_absolute_percentage_error: 28190.6191 - mean_absolute_error: 0.0195 - mean_squared_error: 0.0036 - val_loss: 7.8406e-04 - val_mean_absolute_percentage_error: 62.9025 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.8406e-04\n",
      "Epoch 410/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0243 - mean_absolute_percentage_error: 23.3608 - mean_absolute_error: 0.0407 - mean_squared_error: 0.0243",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28647.9570 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.7493e-04 - val_mean_absolute_percentage_error: 62.5936 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.7493e-04\n",
      "Epoch 411/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.0965e-04 - mean_absolute_percentage_error: 31.0120 - mean_absolute_error: 0.0157 - mean_squared_error: 5.0965e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28304.6992 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.6486e-04 - val_mean_absolute_percentage_error: 62.2518 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.6486e-04\n",
      "Epoch 412/500\n\r",
      " 32/289 [==>...........................] - ETA: 0s - loss: 0.0030 - mean_absolute_percentage_error: 29.7937 - mean_absolute_error: 0.0246 - mean_squared_error: 0.0030",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27943.1289 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.5512e-04 - val_mean_absolute_percentage_error: 61.8241 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.5512e-04\n",
      "Epoch 413/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.4215e-04 - mean_absolute_percentage_error: 252176.7812 - mean_absolute_error: 0.0139 - mean_squared_error: 4.4215e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27954.0781 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.6185e-04 - val_mean_absolute_percentage_error: 61.9868 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.6185e-04\n",
      "Epoch 414/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.7815e-04 - mean_absolute_percentage_error: 21.5388 - mean_absolute_error: 0.0107 - mean_squared_error: 2.7815e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27848.1719 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.5243e-04 - val_mean_absolute_percentage_error: 61.1338 - val_mean_absolute_error: 0.0186 - val_mean_squared_error: 7.5243e-04\n",
      "Epoch 415/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.3376e-04 - mean_absolute_percentage_error: 29.9305 - mean_absolute_error: 0.0169 - mean_squared_error: 6.3376e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27764.5938 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.6615e-04 - val_mean_absolute_percentage_error: 61.5762 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.6615e-04\n",
      "Epoch 416/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.8507e-04 - mean_absolute_percentage_error: 28.7163 - mean_absolute_error: 0.0119 - mean_squared_error: 2.8507e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27739.2754 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0035 - val_loss: 7.7198e-04 - val_mean_absolute_percentage_error: 61.7710 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.7198e-04\n",
      "Epoch 417/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0013 - mean_absolute_percentage_error: 20.9821 - mean_absolute_error: 0.0191 - mean_squared_error: 0.0013",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26628.3555 - mean_absolute_error: 0.0194 - mean_squared_error: 0.0035 - val_loss: 7.6754e-04 - val_mean_absolute_percentage_error: 60.1533 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.6754e-04\n",
      "Epoch 418/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.0726e-04 - mean_absolute_percentage_error: 55.9459 - mean_absolute_error: 0.0138 - mean_squared_error: 4.0726e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26839.4512 - mean_absolute_error: 0.0193 - mean_squared_error: 0.0035 - val_loss: 7.7906e-04 - val_mean_absolute_percentage_error: 61.4874 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.7906e-04\n",
      "Epoch 419/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0247 - mean_absolute_percentage_error: 45.8297 - mean_absolute_error: 0.0428 - mean_squared_error: 0.0247",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28164.3672 - mean_absolute_error: 0.0195 - mean_squared_error: 0.0035 - val_loss: 7.8846e-04 - val_mean_absolute_percentage_error: 62.8621 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 7.8846e-04\n",
      "Epoch 420/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0033 - mean_absolute_percentage_error: 38.9819 - mean_absolute_error: 0.0273 - mean_squared_error: 0.0033",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27919.8555 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.8608e-04 - val_mean_absolute_percentage_error: 62.6459 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.8608e-04\n",
      "Epoch 421/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0013 - mean_absolute_percentage_error: 253128.7969 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0013",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 183us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28059.6895 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.8328e-04 - val_mean_absolute_percentage_error: 62.7491 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.8328e-04\n",
      "Epoch 422/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.4272e-04 - mean_absolute_percentage_error: 22.8766 - mean_absolute_error: 0.0125 - mean_squared_error: 3.4272e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28095.2051 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.7991e-04 - val_mean_absolute_percentage_error: 62.4248 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.7991e-04\n",
      "Epoch 423/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.8388e-04 - mean_absolute_percentage_error: 40.1555 - mean_absolute_error: 0.0156 - mean_squared_error: 5.8388e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27743.9844 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.6987e-04 - val_mean_absolute_percentage_error: 61.1742 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.6987e-04\n",
      "Epoch 424/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.5599e-04 - mean_absolute_percentage_error: 30.2101 - mean_absolute_error: 0.0134 - mean_squared_error: 3.5599e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27643.8340 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.7510e-04 - val_mean_absolute_percentage_error: 61.7643 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.7510e-04\n",
      "Epoch 425/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.0723e-04 - mean_absolute_percentage_error: 23.6607 - mean_absolute_error: 0.0146 - mean_squared_error: 5.0723e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27224.6758 - mean_absolute_error: 0.0195 - mean_squared_error: 0.0035 - val_loss: 7.6937e-04 - val_mean_absolute_percentage_error: 60.3218 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.6937e-04\n",
      "Epoch 426/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.8374e-04 - mean_absolute_percentage_error: 23.4542 - mean_absolute_error: 0.0107 - mean_squared_error: 2.8374e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26905.3867 - mean_absolute_error: 0.0193 - mean_squared_error: 0.0035 - val_loss: 7.7197e-04 - val_mean_absolute_percentage_error: 60.4943 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.7197e-04\n",
      "Epoch 427/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.7910e-04 - mean_absolute_percentage_error: 64.4655 - mean_absolute_error: 0.0170 - mean_squared_error: 5.7910e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27656.6133 - mean_absolute_error: 0.0194 - mean_squared_error: 0.0035 - val_loss: 7.7807e-04 - val_mean_absolute_percentage_error: 62.5399 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.7807e-04\n",
      "Epoch 428/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.4447e-04 - mean_absolute_percentage_error: 39.0810 - mean_absolute_error: 0.0174 - mean_squared_error: 5.4447e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28607.7773 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 8.2683e-04 - val_mean_absolute_percentage_error: 64.5881 - val_mean_absolute_error: 0.0198 - val_mean_squared_error: 8.2683e-04\n",
      "Epoch 429/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0028 - mean_absolute_percentage_error: 28.1189 - mean_absolute_error: 0.0227 - mean_squared_error: 0.0028",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 189us/sample - loss: 0.0035 - mean_absolute_percentage_error: 29038.1074 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0035 - val_loss: 8.2221e-04 - val_mean_absolute_percentage_error: 64.1351 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 8.2221e-04\n",
      "Epoch 430/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0028 - mean_absolute_percentage_error: 27.2502 - mean_absolute_error: 0.0224 - mean_squared_error: 0.0028",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28446.5020 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.5357e-04 - val_mean_absolute_percentage_error: 60.6084 - val_mean_absolute_error: 0.0187 - val_mean_squared_error: 7.5357e-04\n",
      "Epoch 431/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.4957e-04 - mean_absolute_percentage_error: 17.3215 - mean_absolute_error: 0.0126 - mean_squared_error: 3.4957e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 189us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26394.1309 - mean_absolute_error: 0.0195 - mean_squared_error: 0.0035 - val_loss: 7.3875e-04 - val_mean_absolute_percentage_error: 59.5052 - val_mean_absolute_error: 0.0185 - val_mean_squared_error: 7.3875e-04\n",
      "Epoch 432/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0243 - mean_absolute_percentage_error: 28.1175 - mean_absolute_error: 0.0402 - mean_squared_error: 0.0243",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27641.0898 - mean_absolute_error: 0.0195 - mean_squared_error: 0.0035 - val_loss: 7.5414e-04 - val_mean_absolute_percentage_error: 61.5627 - val_mean_absolute_error: 0.0186 - val_mean_squared_error: 7.5414e-04\n",
      "Epoch 433/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.2151e-04 - mean_absolute_percentage_error: 31.7217 - mean_absolute_error: 0.0157 - mean_squared_error: 5.2151e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 199us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28131.2559 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.5210e-04 - val_mean_absolute_percentage_error: 61.4736 - val_mean_absolute_error: 0.0186 - val_mean_squared_error: 7.5210e-04\n",
      "Epoch 434/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.3297e-04 - mean_absolute_percentage_error: 22.2122 - mean_absolute_error: 0.0153 - mean_squared_error: 6.3297e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27920.6309 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.6521e-04 - val_mean_absolute_percentage_error: 61.7042 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.6521e-04\n",
      "Epoch 435/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.3113e-04 - mean_absolute_percentage_error: 33.1947 - mean_absolute_error: 0.0116 - mean_squared_error: 2.3113e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28060.7734 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.5541e-04 - val_mean_absolute_percentage_error: 61.3411 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.5541e-04\n",
      "Epoch 436/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.6106e-04 - mean_absolute_percentage_error: 32.1831 - mean_absolute_error: 0.0163 - mean_squared_error: 5.6106e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28115.2461 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.7408e-04 - val_mean_absolute_percentage_error: 62.6182 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.7408e-04\n",
      "Epoch 437/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 8.8954e-04 - mean_absolute_percentage_error: 77.0233 - mean_absolute_error: 0.0210 - mean_squared_error: 8.8954e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28232.8379 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.7247e-04 - val_mean_absolute_percentage_error: 61.7700 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.7247e-04\n",
      "Epoch 438/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.6247e-04 - mean_absolute_percentage_error: 30.1188 - mean_absolute_error: 0.0143 - mean_squared_error: 3.6247e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 194us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27825.3848 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.9080e-04 - val_mean_absolute_percentage_error: 62.8975 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.9080e-04\n",
      "Epoch 439/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.0365e-04 - mean_absolute_percentage_error: 53.3203 - mean_absolute_error: 0.0106 - mean_squared_error: 2.0365e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28615.8262 - mean_absolute_error: 0.0201 - mean_squared_error: 0.0035 - val_loss: 8.1811e-04 - val_mean_absolute_percentage_error: 63.5801 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 8.1811e-04\n",
      "Epoch 440/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 3.4294e-04 - mean_absolute_percentage_error: 17.9150 - mean_absolute_error: 0.0121 - mean_squared_error: 3.4294e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28280.2578 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 8.0233e-04 - val_mean_absolute_percentage_error: 61.3443 - val_mean_absolute_error: 0.0195 - val_mean_squared_error: 8.0233e-04\n",
      "Epoch 441/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.7003e-04 - mean_absolute_percentage_error: 23.0547 - mean_absolute_error: 0.0155 - mean_squared_error: 4.7003e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27025.7559 - mean_absolute_error: 0.0194 - mean_squared_error: 0.0035 - val_loss: 7.6909e-04 - val_mean_absolute_percentage_error: 60.6698 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.6909e-04\n",
      "Epoch 442/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.6489e-04 - mean_absolute_percentage_error: 22.3499 - mean_absolute_error: 0.0169 - mean_squared_error: 4.6489e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 182us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27751.6738 - mean_absolute_error: 0.0195 - mean_squared_error: 0.0035 - val_loss: 7.7168e-04 - val_mean_absolute_percentage_error: 61.8856 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.7168e-04\n",
      "Epoch 443/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.0285e-04 - mean_absolute_percentage_error: 43.0183 - mean_absolute_error: 0.0153 - mean_squared_error: 6.0285e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27039.8105 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.8703e-04 - val_mean_absolute_percentage_error: 60.4438 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.8703e-04\n",
      "Epoch 444/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 1.8451e-04 - mean_absolute_percentage_error: 21.7244 - mean_absolute_error: 0.0102 - mean_squared_error: 1.8451e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26542.9316 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.8347e-04 - val_mean_absolute_percentage_error: 60.7012 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.8347e-04\n",
      "Epoch 445/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.4845e-04 - mean_absolute_percentage_error: 38.3012 - mean_absolute_error: 0.0170 - mean_squared_error: 5.4845e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27903.3555 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0035 - val_loss: 7.7785e-04 - val_mean_absolute_percentage_error: 63.5728 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 7.7785e-04\n",
      "Epoch 446/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.6009e-04 - mean_absolute_percentage_error: 24.2103 - mean_absolute_error: 0.0145 - mean_squared_error: 5.6009e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28309.4961 - mean_absolute_error: 0.0202 - mean_squared_error: 0.0035 - val_loss: 7.4566e-04 - val_mean_absolute_percentage_error: 61.3272 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.4566e-04\n",
      "Epoch 447/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 2.5517e-04 - mean_absolute_percentage_error: 26.8700 - mean_absolute_error: 0.0102 - mean_squared_error: 2.5517e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26479.8574 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.2067e-04 - val_mean_absolute_percentage_error: 59.4773 - val_mean_absolute_error: 0.0184 - val_mean_squared_error: 7.2067e-04\n",
      "Epoch 448/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.3185e-04 - mean_absolute_percentage_error: 22.4274 - mean_absolute_error: 0.0133 - mean_squared_error: 4.3185e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26392.7949 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.3427e-04 - val_mean_absolute_percentage_error: 60.2505 - val_mean_absolute_error: 0.0187 - val_mean_squared_error: 7.3427e-04\n",
      "Epoch 449/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.9253e-04 - mean_absolute_percentage_error: 37.5085 - mean_absolute_error: 0.0153 - mean_squared_error: 3.9253e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27344.1641 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.4751e-04 - val_mean_absolute_percentage_error: 61.0624 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.4751e-04\n",
      "Epoch 450/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.5768e-04 - mean_absolute_percentage_error: 31.8088 - mean_absolute_error: 0.0150 - mean_squared_error: 4.5768e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27239.3828 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.4660e-04 - val_mean_absolute_percentage_error: 60.1757 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.4660e-04\n",
      "Epoch 451/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0013 - mean_absolute_percentage_error: 27.3829 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0013",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26518.7266 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.5330e-04 - val_mean_absolute_percentage_error: 60.0010 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.5330e-04\n",
      "Epoch 452/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.7395e-04 - mean_absolute_percentage_error: 32.2251 - mean_absolute_error: 0.0124 - mean_squared_error: 2.7395e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26375.5664 - mean_absolute_error: 0.0195 - mean_squared_error: 0.0035 - val_loss: 7.4950e-04 - val_mean_absolute_percentage_error: 60.2331 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.4950e-04\n",
      "Epoch 453/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.6610e-04 - mean_absolute_percentage_error: 242115.5781 - mean_absolute_error: 0.0189 - mean_squared_error: 6.6610e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 183us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26840.4023 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.7829e-04 - val_mean_absolute_percentage_error: 62.7590 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.7829e-04\n",
      "Epoch 454/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.9209e-04 - mean_absolute_percentage_error: 34.2456 - mean_absolute_error: 0.0180 - mean_squared_error: 5.9209e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 180us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28428.6230 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.8078e-04 - val_mean_absolute_percentage_error: 62.9267 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.8078e-04\n",
      "Epoch 455/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.9124e-04 - mean_absolute_percentage_error: 27.8749 - mean_absolute_error: 0.0138 - mean_squared_error: 3.9124e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 28671.7930 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0035 - val_loss: 7.6297e-04 - val_mean_absolute_percentage_error: 62.2937 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.6297e-04\n",
      "Epoch 456/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.1385e-04 - mean_absolute_percentage_error: 34.2078 - mean_absolute_error: 0.0136 - mean_squared_error: 4.1385e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27095.8418 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0035 - val_loss: 7.4025e-04 - val_mean_absolute_percentage_error: 57.4785 - val_mean_absolute_error: 0.0186 - val_mean_squared_error: 7.4025e-04\n",
      "Epoch 457/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.6568e-04 - mean_absolute_percentage_error: 49.5454 - mean_absolute_error: 0.0159 - mean_squared_error: 3.6568e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27012.7656 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0035 - val_loss: 7.5623e-04 - val_mean_absolute_percentage_error: 58.3632 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.5623e-04\n",
      "Epoch 458/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.1672e-04 - mean_absolute_percentage_error: 20.0539 - mean_absolute_error: 0.0141 - mean_squared_error: 3.1672e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26900.6465 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.4257e-04 - val_mean_absolute_percentage_error: 59.1585 - val_mean_absolute_error: 0.0187 - val_mean_squared_error: 7.4257e-04\n",
      "Epoch 459/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0031 - mean_absolute_percentage_error: 29.5067 - mean_absolute_error: 0.0258 - mean_squared_error: 0.0031",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27489.8691 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.5550e-04 - val_mean_absolute_percentage_error: 60.7127 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.5550e-04\n",
      "Epoch 460/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0015 - mean_absolute_percentage_error: 28.1813 - mean_absolute_error: 0.0236 - mean_squared_error: 0.0015",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 190us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27810.5566 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.7135e-04 - val_mean_absolute_percentage_error: 61.3875 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.7135e-04\n",
      "Epoch 461/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0240 - mean_absolute_percentage_error: 36.4317 - mean_absolute_error: 0.0411 - mean_squared_error: 0.0240",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27389.7188 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0035 - val_loss: 7.7348e-04 - val_mean_absolute_percentage_error: 61.3059 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.7348e-04\n",
      "Epoch 462/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.1809e-04 - mean_absolute_percentage_error: 27.3816 - mean_absolute_error: 0.0144 - mean_squared_error: 4.1809e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 180us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26930.1406 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.6743e-04 - val_mean_absolute_percentage_error: 60.3539 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.6743e-04\n",
      "Epoch 463/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.7354e-04 - mean_absolute_percentage_error: 24.4996 - mean_absolute_error: 0.0141 - mean_squared_error: 4.7354e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26132.2793 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.7435e-04 - val_mean_absolute_percentage_error: 60.6794 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.7435e-04\n",
      "Epoch 464/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0015 - mean_absolute_percentage_error: 30.5361 - mean_absolute_error: 0.0246 - mean_squared_error: 0.0015",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27175.7871 - mean_absolute_error: 0.0201 - mean_squared_error: 0.0035 - val_loss: 8.8496e-04 - val_mean_absolute_percentage_error: 64.0457 - val_mean_absolute_error: 0.0205 - val_mean_squared_error: 8.8496e-04\n",
      "Epoch 465/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.3484e-04 - mean_absolute_percentage_error: 21.4574 - mean_absolute_error: 0.0132 - mean_squared_error: 3.3484e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27090.5312 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0035 - val_loss: 8.8599e-04 - val_mean_absolute_percentage_error: 63.2916 - val_mean_absolute_error: 0.0206 - val_mean_squared_error: 8.8599e-04\n",
      "Epoch 466/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 4.4615e-04 - mean_absolute_percentage_error: 242368.0312 - mean_absolute_error: 0.0158 - mean_squared_error: 4.4615e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 188us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26863.5879 - mean_absolute_error: 0.0202 - mean_squared_error: 0.0035 - val_loss: 8.5344e-04 - val_mean_absolute_percentage_error: 60.7133 - val_mean_absolute_error: 0.0203 - val_mean_squared_error: 8.5344e-04\n",
      "Epoch 467/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.4997e-04 - mean_absolute_percentage_error: 20.3168 - mean_absolute_error: 0.0158 - mean_squared_error: 4.4997e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25080.5840 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0035 - val_loss: 8.1396e-04 - val_mean_absolute_percentage_error: 59.2473 - val_mean_absolute_error: 0.0197 - val_mean_squared_error: 8.1396e-04\n",
      "Epoch 468/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.2388e-04 - mean_absolute_percentage_error: 22.4627 - mean_absolute_error: 0.0184 - mean_squared_error: 5.2388e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 198us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25820.0332 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0035 - val_loss: 8.3294e-04 - val_mean_absolute_percentage_error: 60.1027 - val_mean_absolute_error: 0.0199 - val_mean_squared_error: 8.3294e-04\n",
      "Epoch 469/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.3804e-04 - mean_absolute_percentage_error: 39.1762 - mean_absolute_error: 0.0144 - mean_squared_error: 5.3804e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25632.3984 - mean_absolute_error: 0.0194 - mean_squared_error: 0.0035 - val_loss: 8.1135e-04 - val_mean_absolute_percentage_error: 58.2006 - val_mean_absolute_error: 0.0196 - val_mean_squared_error: 8.1135e-04\n",
      "Epoch 470/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.2718e-04 - mean_absolute_percentage_error: 26.7409 - mean_absolute_error: 0.0112 - mean_squared_error: 2.2718e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25701.0801 - mean_absolute_error: 0.0191 - mean_squared_error: 0.0035 - val_loss: 8.1986e-04 - val_mean_absolute_percentage_error: 60.3704 - val_mean_absolute_error: 0.0199 - val_mean_squared_error: 8.1986e-04\n",
      "Epoch 471/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0240 - mean_absolute_percentage_error: 27.1730 - mean_absolute_error: 0.0366 - mean_squared_error: 0.0240",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26544.7793 - mean_absolute_error: 0.0193 - mean_squared_error: 0.0035 - val_loss: 7.9366e-04 - val_mean_absolute_percentage_error: 59.8991 - val_mean_absolute_error: 0.0195 - val_mean_squared_error: 7.9366e-04\n",
      "Epoch 472/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.2390e-04 - mean_absolute_percentage_error: 29.3708 - mean_absolute_error: 0.0157 - mean_squared_error: 6.2390e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26378.7520 - mean_absolute_error: 0.0193 - mean_squared_error: 0.0035 - val_loss: 7.6626e-04 - val_mean_absolute_percentage_error: 58.9963 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.6626e-04\n",
      "Epoch 473/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0243 - mean_absolute_percentage_error: 29.9180 - mean_absolute_error: 0.0446 - mean_squared_error: 0.0243",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27026.0684 - mean_absolute_error: 0.0195 - mean_squared_error: 0.0035 - val_loss: 7.6318e-04 - val_mean_absolute_percentage_error: 59.7865 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.6318e-04\n",
      "Epoch 474/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.7584e-04 - mean_absolute_percentage_error: 46.2248 - mean_absolute_error: 0.0166 - mean_squared_error: 5.7584e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 189us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26491.4453 - mean_absolute_error: 0.0194 - mean_squared_error: 0.0035 - val_loss: 7.5444e-04 - val_mean_absolute_percentage_error: 58.7391 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.5444e-04\n",
      "Epoch 475/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.8529e-04 - mean_absolute_percentage_error: 39.4324 - mean_absolute_error: 0.0128 - mean_squared_error: 2.8529e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26404.0488 - mean_absolute_error: 0.0193 - mean_squared_error: 0.0035 - val_loss: 7.6239e-04 - val_mean_absolute_percentage_error: 59.3635 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.6239e-04\n",
      "Epoch 476/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 8.6439e-04 - mean_absolute_percentage_error: 19.8357 - mean_absolute_error: 0.0204 - mean_squared_error: 8.6439e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27183.8477 - mean_absolute_error: 0.0194 - mean_squared_error: 0.0035 - val_loss: 7.7804e-04 - val_mean_absolute_percentage_error: 61.0756 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.7804e-04\n",
      "Epoch 477/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.4627e-04 - mean_absolute_percentage_error: 60.3339 - mean_absolute_error: 0.0132 - mean_squared_error: 3.4627e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 188us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27624.8613 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.8115e-04 - val_mean_absolute_percentage_error: 61.0504 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.8115e-04\n",
      "Epoch 478/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.9119e-04 - mean_absolute_percentage_error: 21.2025 - mean_absolute_error: 0.0132 - mean_squared_error: 3.9119e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 190us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26907.5703 - mean_absolute_error: 0.0197 - mean_squared_error: 0.0035 - val_loss: 7.6548e-04 - val_mean_absolute_percentage_error: 59.8836 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.6548e-04\n",
      "Epoch 479/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 7.6856e-04 - mean_absolute_percentage_error: 23.4247 - mean_absolute_error: 0.0186 - mean_squared_error: 7.6856e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 191us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25960.9707 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.5634e-04 - val_mean_absolute_percentage_error: 59.3719 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.5634e-04\n",
      "Epoch 480/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0031 - mean_absolute_percentage_error: 237648.3906 - mean_absolute_error: 0.0263 - mean_squared_error: 0.0031",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 201us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26344.7188 - mean_absolute_error: 0.0198 - mean_squared_error: 0.0035 - val_loss: 7.9661e-04 - val_mean_absolute_percentage_error: 62.0331 - val_mean_absolute_error: 0.0195 - val_mean_squared_error: 7.9661e-04\n",
      "Epoch 481/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 7.2517e-04 - mean_absolute_percentage_error: 22.6024 - mean_absolute_error: 0.0165 - mean_squared_error: 7.2517e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 180us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27402.3047 - mean_absolute_error: 0.0205 - mean_squared_error: 0.0035 - val_loss: 8.1902e-04 - val_mean_absolute_percentage_error: 63.8933 - val_mean_absolute_error: 0.0198 - val_mean_squared_error: 8.1902e-04\n",
      "Epoch 482/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 3.5183e-04 - mean_absolute_percentage_error: 44.9516 - mean_absolute_error: 0.0142 - mean_squared_error: 3.5183e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26979.0684 - mean_absolute_error: 0.0202 - mean_squared_error: 0.0035 - val_loss: 7.8888e-04 - val_mean_absolute_percentage_error: 61.2682 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.8888e-04\n",
      "Epoch 483/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0239 - mean_absolute_percentage_error: 47.4824 - mean_absolute_error: 0.0440 - mean_squared_error: 0.0239",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 189us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25773.9199 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0035 - val_loss: 7.7158e-04 - val_mean_absolute_percentage_error: 59.8828 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.7158e-04\n",
      "Epoch 484/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 7.5387e-04 - mean_absolute_percentage_error: 21.9930 - mean_absolute_error: 0.0174 - mean_squared_error: 7.5387e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 185us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25371.2207 - mean_absolute_error: 0.0194 - mean_squared_error: 0.0035 - val_loss: 7.6904e-04 - val_mean_absolute_percentage_error: 59.3554 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.6904e-04\n",
      "Epoch 485/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0243 - mean_absolute_percentage_error: 23.1618 - mean_absolute_error: 0.0416 - mean_squared_error: 0.0243",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25761.7910 - mean_absolute_error: 0.0193 - mean_squared_error: 0.0035 - val_loss: 7.9185e-04 - val_mean_absolute_percentage_error: 59.9282 - val_mean_absolute_error: 0.0193 - val_mean_squared_error: 7.9185e-04\n",
      "Epoch 486/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 5.0394e-04 - mean_absolute_percentage_error: 26.5913 - mean_absolute_error: 0.0136 - mean_squared_error: 5.0394e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25562.1133 - mean_absolute_error: 0.0192 - mean_squared_error: 0.0035 - val_loss: 7.9610e-04 - val_mean_absolute_percentage_error: 59.6050 - val_mean_absolute_error: 0.0194 - val_mean_squared_error: 7.9610e-04\n",
      "Epoch 487/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0011 - mean_absolute_percentage_error: 230186.6562 - mean_absolute_error: 0.0191 - mean_squared_error: 0.0011",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 193us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25518.7500 - mean_absolute_error: 0.0191 - mean_squared_error: 0.0035 - val_loss: 7.8962e-04 - val_mean_absolute_percentage_error: 59.9734 - val_mean_absolute_error: 0.0194 - val_mean_squared_error: 7.8962e-04\n",
      "Epoch 488/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.3837e-04 - mean_absolute_percentage_error: 26.2002 - mean_absolute_error: 0.0151 - mean_squared_error: 6.3837e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25204.9414 - mean_absolute_error: 0.0189 - mean_squared_error: 0.0035 - val_loss: 7.4859e-04 - val_mean_absolute_percentage_error: 58.6711 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.4859e-04\n",
      "Epoch 489/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 0.0013 - mean_absolute_percentage_error: 27.5904 - mean_absolute_error: 0.0201 - mean_squared_error: 0.0013",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 25769.1133 - mean_absolute_error: 0.0190 - mean_squared_error: 0.0035 - val_loss: 7.5512e-04 - val_mean_absolute_percentage_error: 60.9591 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.5512e-04\n",
      "Epoch 490/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.9272e-04 - mean_absolute_percentage_error: 40.6765 - mean_absolute_error: 0.0165 - mean_squared_error: 6.9272e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26629.4082 - mean_absolute_error: 0.0192 - mean_squared_error: 0.0035 - val_loss: 7.5041e-04 - val_mean_absolute_percentage_error: 60.4535 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.5041e-04\n",
      "Epoch 491/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 6.9826e-04 - mean_absolute_percentage_error: 28.3560 - mean_absolute_error: 0.0160 - mean_squared_error: 6.9826e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 187us/sample - loss: 0.0035 - mean_absolute_percentage_error: 27316.0742 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0035 - val_loss: 7.7695e-04 - val_mean_absolute_percentage_error: 61.9241 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.7695e-04\n",
      "Epoch 492/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.4012e-04 - mean_absolute_percentage_error: 62.1046 - mean_absolute_error: 0.0139 - mean_squared_error: 3.4012e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 186us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26193.0293 - mean_absolute_error: 0.0194 - mean_squared_error: 0.0035 - val_loss: 7.5272e-04 - val_mean_absolute_percentage_error: 58.4765 - val_mean_absolute_error: 0.0189 - val_mean_squared_error: 7.5272e-04\n",
      "Epoch 493/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.1645e-04 - mean_absolute_percentage_error: 34.4043 - mean_absolute_error: 0.0155 - mean_squared_error: 4.1645e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26967.0527 - mean_absolute_error: 0.0194 - mean_squared_error: 0.0035 - val_loss: 7.6703e-04 - val_mean_absolute_percentage_error: 60.2380 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.6703e-04\n",
      "Epoch 494/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.7950e-04 - mean_absolute_percentage_error: 27.7374 - mean_absolute_error: 0.0132 - mean_squared_error: 3.7950e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 182us/sample - loss: 0.0034 - mean_absolute_percentage_error: 26945.8086 - mean_absolute_error: 0.0195 - mean_squared_error: 0.0034 - val_loss: 7.6671e-04 - val_mean_absolute_percentage_error: 60.5916 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.6671e-04\n",
      "Epoch 495/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 7.0453e-04 - mean_absolute_percentage_error: 35.3654 - mean_absolute_error: 0.0168 - mean_squared_error: 7.0453e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 204us/sample - loss: 0.0034 - mean_absolute_percentage_error: 27031.2812 - mean_absolute_error: 0.0195 - mean_squared_error: 0.0034 - val_loss: 7.5973e-04 - val_mean_absolute_percentage_error: 61.0881 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.5973e-04\n",
      "Epoch 496/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 2.5993e-04 - mean_absolute_percentage_error: 59.4566 - mean_absolute_error: 0.0112 - mean_squared_error: 2.5993e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 205us/sample - loss: 0.0034 - mean_absolute_percentage_error: 27848.3457 - mean_absolute_error: 0.0200 - mean_squared_error: 0.0034 - val_loss: 7.7432e-04 - val_mean_absolute_percentage_error: 62.1846 - val_mean_absolute_error: 0.0192 - val_mean_squared_error: 7.7432e-04\n",
      "Epoch 497/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 3.4865e-04 - mean_absolute_percentage_error: 33.9892 - mean_absolute_error: 0.0134 - mean_squared_error: 3.4865e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b",
      "\r289/289 [==============================] - 0s 194us/sample - loss: 0.0034 - mean_absolute_percentage_error: 26683.4980 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0034 - val_loss: 7.6796e-04 - val_mean_absolute_percentage_error: 60.5454 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.6796e-04\n",
      "Epoch 498/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 4.5254e-04 - mean_absolute_percentage_error: 33.2684 - mean_absolute_error: 0.0151 - mean_squared_error: 4.5254e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 190us/sample - loss: 0.0034 - mean_absolute_percentage_error: 26012.5430 - mean_absolute_error: 0.0196 - mean_squared_error: 0.0034 - val_loss: 7.5841e-04 - val_mean_absolute_percentage_error: 60.4002 - val_mean_absolute_error: 0.0190 - val_mean_squared_error: 7.5841e-04\n",
      "Epoch 499/500\n",
      "\r 32/289 [==>...........................] - ETA: 0s - loss: 3.5939e-04 - mean_absolute_percentage_error: 37.9159 - mean_absolute_error: 0.0133 - mean_squared_error: 3.5939e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 189us/sample - loss: 0.0034 - mean_absolute_percentage_error: 27273.3535 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0034 - val_loss: 7.4694e-04 - val_mean_absolute_percentage_error: 62.5082 - val_mean_absolute_error: 0.0191 - val_mean_squared_error: 7.4694e-04\n",
      "Epoch 500/500\n\r 32/289 [==>...........................] - ETA: 0s - loss: 2.4540e-04 - mean_absolute_percentage_error: 26.2371 - mean_absolute_error: 0.0108 - mean_squared_error: 2.4540e-04",
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r289/289 [==============================] - 0s 184us/sample - loss: 0.0035 - mean_absolute_percentage_error: 26382.0625 - mean_absolute_error: 0.0199 - mean_squared_error: 0.0035 - val_loss: 7.3383e-04 - val_mean_absolute_percentage_error: 60.2403 - val_mean_absolute_error: 0.0188 - val_mean_squared_error: 7.3383e-04\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 576x576 with 2 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "model = train_model(trainX, trainY, testX, testY,model,show_plot=True,epochs=500,batch_size=32)\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "name": "stdout",
     "text": [
      "rms=157713.97, r_value = 0.91, p_value = 0.00, y=0.88*x + 84206.01 \n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x432 with 3 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "evaluate_regression_model(model,testX,testY,normalizer,show_plot=True)\n",
    "model.save('regression_model_data.h5')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  }
 ],
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  },
  "kernelspec": {
   "name": "python3",
   "language": "python",
   "display_name": "Python 3"
  },
  "pycharm": {
   "stem_cell": {
    "cell_type": "raw",
    "source": [],
    "metadata": {
     "collapsed": false
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}