bert_finetune6.ipynb

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     "text": [
      "Epoch 1/4\n",
      "140/140 [==============================] - 313s 2s/step - loss: 0.0299 - accuracy: 0.9930 - val_loss: 0.0700 - val_accuracy: 0.9839\n",
      "Epoch 2/4\n",
      "140/140 [==============================] - 333s 2s/step - loss: 0.0207 - accuracy: 0.9948 - val_loss: 0.0563 - val_accuracy: 0.9865\n",
      "Epoch 3/4\n",
      "140/140 [==============================] - 349s 2s/step - loss: 0.0180 - accuracy: 0.9960 - val_loss: 0.0696 - val_accuracy: 0.9848\n",
      "Epoch 4/4\n",
      "140/140 [==============================] - 348s 2s/step - loss: 0.0064 - accuracy: 0.9991 - val_loss: 0.0792 - val_accuracy: 0.9865\n"
     ]
    }
   ],
   "source": [
    "history=bert_model.fit([train_inp,train_mask],train_label,batch_size=32,epochs=4,validation_data=([val_inp,val_mask],val_label),callbacks=callbacks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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