Google Metrax Brings Predefined Model Evaluation Metrics to JAX

Recently open-sourced by Google, Metrax is a JAX library providing standardized, performant metrics implementations for classification, regression, NLP, vision, and audio models.

Metrax addresses a gap in the JAX ecosystem, explains Google, that has forced many teams migrating from TensorFlow to JAX to implement they own versions of common evaluation metrics such as accuracy, F1, RMS error, and others:

While creating metrics may seem, to some, like a fairly simple and straightforward topic, when considering large scale training and evaluation across datacenter-sized distributed compute environments, it becomes somewhat less trivial.

Metrax provides predefined evaluation metrics for a range of machine learning models, including classification, regression, recommendation, vision, and audio, with particular support for distributed and large-scale training environments. For vision models, the library includes metrics such as Intersection over Union (IoU),…