# a check point callback to save our best weights

checkpoint = ModelCheckpoint('dog_breed_classifier_model.h5', 

                             monitor='val_acc', 

                             verbose=1, 

                             save_best_only=True, 

                             mode='max', 

                             save_weights_only=True)

​

# a reducing lr callback to reduce lr when val_loss doesn't increase

reduce_lr = ReduceLROnPlateau(monitor='val_loss', factor=0.2,

                                   patience=1, verbose=1, mode='min',

                                   min_delta=0.0001, cooldown=2, min_lr=1e-7)

​

# for early stop

early_stop = EarlyStopping(monitor="val_loss", mode="min", patience=5)