metrics.help – Machine learning training metrics explained without heavy math

Summary: metrics.help provides clear, math-free explanations and visualizations of common machine learning training metrics. It covers key metrics like KL Divergence, Gradient Norm, and Clip Ratio, illustrating healthy and unhealthy training progressions to aid understanding.

What it does

It explains ML training metrics with simple definitions and visual graphs, including reinforcement learning algorithms. Users can paste log outputs to quickly assess their training steps.

Who it's for

Designed for machine learning practitioners seeking straightforward explanations of training metrics during model development.

Why it matters

It fills the gap for accessible, non-mathematical resources to interpret ML training metrics and monitor model progress effectively.