Build a Small Golden Eval Set Before Tuning
Create a practical golden evaluation set for a RAG pipeline using evidence IDs and failure categories.
Alina needs to prove whether a retriever change improved the benefits assistant, but every demo uses different questions. Golden RAG eval: question -> expected evidence -> expected behavior -> failure tag The common trap is scoring only final answer vibes. A fluent answer can hide missing evidence, stale citations, or unsupported numbers. Define query classes Create a balanced set: exact lookup, paraphrase, conflict, multi-hop, and no-answer cases. A RAG system can improve one class while regressing another. Query classes make that tradeoff visible. Attach evidence IDs For every answerable question, record the source document ID, section, and expected evidence span.…
Sign up free — one personalized lesson every day, matched to your role and goals.
Already have an account? Sign in