This tutorial explains how early stopping is implemented in TensorFlow. The key lesson is to use tf.keras.EarlyStopping callback. Early stopping is triggered by monitoring if a certain quantity has improved over the latest period of time.
This tutorial explains how to use checkpoints to save and restore TensorFlow models during the training. The key is to use tf.kears.ModelCheckpoint callbacks to save the model. Set initial_epoch in the model.fit call to restore the model from a pre-saved checkpoint.
This tutorial explains how to do transfer learning with TensorFlow 2. We cover handling customized datasets, restoring backbone with Keras's application API, and restoring backbone from the disk.
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