model_fit.py

customAdam = keras.optimizers.Adam(lr=0.0001) 
model.compile(optimizer=customAdam, 
              # Loss function to minimize
              loss="binary_crossentropy",
              # List of metrics to monitor
              metrics=["mean_squared_error","binary_crossentropy"])

es = keras.callbacks.EarlyStopping(monitor='loss', mode='min', verbose=1, patience = 5)
print('# Fit model on training data')

history = model.fit(X, 
                    y, 
                    batch_size=512, 
                    epochs=500,
                    validation_split=0.1,
                    callbacks = [es]
                   )