Resumable Training and Incremental Training

Overview

Resumable training indicates that an interrupted training job can be automatically resumed from the checkpoint where the previous training was interrupted. This method is applicable to model training that takes a long time.

Incremental training is a method in which input data is continuously used to extend the existing model's knowledge to further train the model.

Checkpoints are used to resume model training or incrementally train a model.

During model training, training results (including but not limited to epochs, model weights, optimizer status, and scheduler status) are continuously saved. In this way, an interrupted training job can be automatically resumed from the checkpoint where the previous training was interrupted.

To resume a training job, load a checkpoint and use the checkpoint information to initialize the training status. To do so, add reload ckpt to the code.

Resumable Training and Incremental Training in ModelArts

To resume model training or incrementally train a model in ModelArts, configure Training Output.

When creating a training job, configure the data path to the training output, save checkpoints in this data path, and set Predownload to Yes. If you set Predownload to Yes, the system automatically downloads the checkpoint file in the training output data path to a local directory of the training container before the training job is started.

Figure 1 Configuring training output

Enable fault tolerance check (auto restart) for resumable training. On the training job creation page, enable Auto Restart. If the environment pre-check fails, the hardware is not functional, or the training job fails, ModelArts will automatically issue the training job again.

Figure 2 Auto Restart