LLM Fine-tuning Dataset Version Governance in Production: Using Data Lineage, Evaluation Gates, and Rollback Strategies to Prevent SFT Degradation
A practical guide to versioning LLM fine-tuning datasets in production, covering sample lineage, train-test splits, evaluation gates, experiment tracking, rollback strategies, and pre-release checklists to prevent SFT degradation from dirty data, biased samples, or incorrect labels.