Moviesmobilenet -

# Unfreeze some layers and fine-tune for layer in base.layers[-40:]: layer.trainable = True model.compile(optimizer=tf.keras.optimizers.Adam(1e-5), loss='categorical_crossentropy', metrics=['accuracy']) model.fit(train_ds, validation_data=val_ds, epochs=10) # Export to TFLite converter = tf.lite.TFLiteConverter.from_keras_model(model) converter.optimizations = [tf.lite.Optimize.DEFAULT] tflite_model = converter.convert() open('moviesmobilenet.tflite','wb').write(tflite_model)

: State who would enjoy this content or service (e.g., "best for fans of 90s action" or "ideal for watching on a small screen"). moviesmobilenet

: Use the Moviesmobilenet Glossary to ensure you are using correct industry terminology (e.g., "mise-en-scène," "foley," or "montage"). # Unfreeze some layers and fine-tune for layer in base