Fitting the model and allowing for saving of the model based on the best validation loss

fit_model.py

callbacks = [
    keras.callbacks.ModelCheckpoint(
        filepath=f"{hotDogDir}hotdog_classifier_v1.keras",
        monitor="val_loss",
        save_best_only=True
    )
]

history = model.fit(
    train_dataset,
    epochs=30,
    validation_data=validation_dataset,
    callbacks=callbacks
)