Checkpoint

A checkpoint is a saved point in the process of training a machine learning model. Think of it like bookmarking your progress so you can stop and return later without losing all your work. In practical terms, checkpoints store the model's learned parameters at a certain stage, allowing researchers to pause training, recover from interruptions, or select the best version of the model based on performance. This process helps make training more efficient and provides safety nets against errors or failures.