AI Systems

Fine-Tuning, explained

Fine-tuning adapts a pretrained model by continuing training on task-specific or domain-specific data.
Back to Glossary

Part of the Semantic Notion technical glossary.

Short Definition

Fine-tuning adapts a pretrained model by continuing training on task-specific or domain-specific data.

Intuition

Instead of training from scratch, you start with a broadly capable model and nudge it toward the behavior you need.

Technical Definition

Fine-tuning updates some or all model parameters, or adaptation parameters, using additional supervised, preference, or domain data.

Example

A legal assistant may fine-tune a model on approved drafting examples and review rubrics.

Common Misunderstandings

Fine-tuning is not the right answer for every customization problem.
Fine-tuned models still need evaluation and safety controls.

Start here

Need the broader concept map?

Return to the glossary index to move from this definition into adjacent AI, ML, mathematics, and computer science terms.