Evaluate
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Overview
HEALTH SCORE
Fair
67out of 100
Development cadence drags the score down. Maintainer coverage and security posture help keep it from falling further.
LIFECYCLE
Active
Consistent commits, responsive maintainers, regular releases, and healthy issue triage.
Health breakdown
Fair(67/100)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
Median response time is 22 days.
Bus factor
8 active maintainers currently have merge rights.
Organization Diversity
Contributors span 63 organizations.
Project Achievements
Leaderboards
About
Evaluate is a library that provides tools and utilities for evaluating machine learning models and datasets. It enables users to create, share, and use evaluation methods to assess model performance, data quality, and other metrics in a standardized way.
First commit
Software value
$840K
Tags
evaluation
machine-learning
License(s)
Apache-2.0
Data sources
Git
GitHub