Validates AI model checkpoints against datasets to measure performance and benchmark key metrics.
The run-validation skill streamlines the process of evaluating trained machine learning models by guiding users through checkpoint selection, dataset identification, and metric definition. It supports standard loss and accuracy calculations as well as task-specific metrics like BLEU, ROUGE, and F1 scores. This skill is essential for AI engineers needing to compare model iterations, verify training progress, or conduct comprehensive performance audits before moving models to production.
