Models can support arbitrary classes

Models will now serialize the class names as part of the model checkpoint. This allows us to flexibly include/remove classes from training datasets without worrying about how to map the prediction index to the human-readable class name. This change is not backwards compatible, older model artifacts will not contain the necessary information to load the correct class names.

Experimentation Setup

Basic instrumentation to train models and track experiments.