Training the model

We are taking a batch size of 32 and 6 epochs. We can play with these parameters to increase the accuracy.

Write the following code to train the model:

batch_size = 32
epochs = 6

history = model.fit(x_train,
                    y_train,
                    batch_size= batch_size,
                    epochs = epochs,
                    verbose=1, 
                    validation_data= (x_test, y_test))



score = model.evaluate(x_test, y_test, verbose=0)
print('Test_loss:', score[0])
print('Test_accuracy:', score[1])

Here are the training results:

Fig 6.21: Model training

The training accuracy for the model is 95.84 and the test loss is 0.069.