The Keepsake Python library is used to create experiments and checkpoints in your training script. It also has functions for programmatically analyzing the experiments.
These two modes are comprehensively described below in the Experiment tracking and Analyze and plot experiments sections.
Track experiments: Automatically track code, hyperparameters, training data, weights, metrics, Python dependencies — everything.
Go back in time: Get back the code and weights from any checkpoint if you need to replicate your results or commit to Git after the fact.
Version your models: Model weights are stored on your own Amazon S3 or Google Cloud bucket, so it’s really easy to feed them into production systems.