Definition
Fine-tuning
Fine-tuning is additional training that adapts an existing model to a narrower task, style, domain, or output format. It changes model behavior more permanently than a prompt, but it is not a substitute for clean data, retrieval, evaluation, or governance.
Last updated: 25 June 2026
Why it matters
It keeps teams from fine-tuning when better prompts, retrieval, or workflow design would solve the problem.
Signals to watch
- Training examples are curated
- Model weights or adapters change
- Output style must be repeated at scale