How do you build edge-case datasets for fine-tuning open-weight models?
Humble-Shopping-9495 · reddit · 2026-10-26
A Reddit discussion on the hardest parts of building fine-tuning datasets for open-weight models, centered on five practical questions: identifying and deriving rare edge cases, generating data by hand vs. synthetic vs. real-data mining, quality control for bad samples, knowing when coverage of failure modes is sufficient, and whether adding more edge cases can actually hurt model performance. Useful for developers doing fine-tuning data engineering.
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