Your LLM Eval Set Needs a Manifest
📰 Medium · LLM
Learn why LLM evaluation sets need metadata manifests for effective testing and validation
Action Steps
- Create a metadata manifest for your LLM eval set
- Include document type information in the manifest
- Track failure history and expected behaviour for each example
- Define routing rules and regression risk in the manifest
- Use the manifest to inform and improve your LLM testing and validation
Who Needs to Know This
Data scientists and LLM developers can benefit from this knowledge to improve their model evaluation and testing processes
Key Insight
💡 Metadata manifests can significantly improve the effectiveness of LLM evaluation and testing
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📊 Improve your LLM eval sets with metadata manifests! 🚀
Key Takeaways
Learn why LLM evaluation sets need metadata manifests for effective testing and validation
Full Article
Why every eval example should carry metadata about document type, failure history, expected behaviour, routing rules, and regression risk. Continue reading on Medium »
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