Training phase

The following code block shows how to fit the model on the training dataset. Let's use 20k images from the training dataset to train the VGG-16 model and 5k images as validation dataset to evaluate the model while training. The weights=None parameter value must be passed to the VGG16() function to ensure that the network is trained from scratch. Note, this will take a long time if not run on a GPU, so a GPU is recommended. 

With 20 epochs, the accuracy achieved on the validation dataset is 78.38%. We can tune the hyperparameters to increase the accuracy of the model ...

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