Human Eval Tracker
Track human evaluation scores for AI outputs
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What is Human Evaluation?
Human evaluation is the gold standard for assessing AI output quality. While automated metrics like BLEU or ROUGE provide quick feedback, human judgment captures nuances in quality, relevance, and naturalness that algorithms miss.
This tracker helps you collect human ratings on a 1-5 scale, add notes, and export results for analysis—essential for LLM fine-tuning and prompt optimization.
Rating Scale
5 - Excellent
Perfect response. Accurate, well-written, and fully addresses the input.
3 - Adequate
Acceptable response. Addresses the input but may lack detail or polish.
1 - Poor
Incorrect or irrelevant response. Does not address the input.
Best Practices
- Blind evaluation: Rate outputs without knowing which model generated them.
- Use notes: Document why you rated something low for training data.
- Multiple raters: For production, use 2-3 raters and measure agreement.
- Calibration: Rate a few examples together first to align expectations.
FAQ
How many samples should I evaluate?
For quick checks: 10-20. For statistically significant results: 100+ samples with multiple raters.
What's inter-rater reliability?
How much different raters agree. Use Cohen's Kappa or Krippendorff's Alpha. Export CSV and analyze separately.