<jupyter_start><jupyter_text>Evaluation Accuracy Graph<jupyter_code>plt.plot(history.history['accuracy'])
plt.plot(history.history['val_accuracy'])
plt.title('Training & Validation Accuracy Curve')
plt.ylabel('accuracy')
plt.xlabel('epoch')
plt.legend(['train', 'test'], loc='upper left')
plt.show()<jupyter_output><empty_output><jupyter_text>Loss Graph<jupyter_code>plt.plot(history.history['loss'])
plt.plot(history.history['val_loss'])
plt.title("Training & Validation Loss Curve")
plt.ylabel("loss")
plt.xlabel("epoch")
plt.legend(['train', 'test'], loc='upper left')
plt.show()
# model.save('D:/Projects/Covid19/Model/VGG16Depthwise/VGG16Depthwise_weights.h5')<jupyter_output><empty_output>
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{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '538633', 'license': 'MIT', 'n_tokens_mistral': 278, 'n_tokens_neox': 251, 'n_words': 29, 'path': 'Classification/VGG16Depth+SimpleGen.ipynb', 'repo_name': 'kool7/COVID-19-Segmentation', 'size': '695'}