# What is Fine-Tuning?

A training process that adjusts a pretrained language model's weights on a domain-specific dataset to change its default behavior, style, or task performance.

Source: https://usewire.io/glossary/fine-tuning/
Last updated: 2026-04-14

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Fine-tuning is best suited to changing how a model behaves rather than what it knows. It reliably shifts output format, tone, and narrow task performance, but it struggles to reliably encode new factual knowledge. Research consistently shows RAG outperforms unsupervised fine-tuning for knowledge injection, which is why most production systems fine-tune for behavior and use retrieval for facts.

## Related terms

- [rag](https://usewire.io/glossary/rag/)
- [context-engineering](https://usewire.io/glossary/context-engineering/)