# Fine Tuning

Fine tuning adapts a pretrained model to a narrower task or style using additional examples.

## Why it matters

Fine-tuning can adapt behavior or task performance, but it is not the default fix for missing current knowledge. Teams should compare prompting, retrieval, and fine-tuning on the same evaluation set and account for training data quality and maintenance.

## Example

A company fine-tunes a smaller model on reviewed classification examples after prompt-only performance plateaus, while policy facts remain in a retrieved knowledge source.

## FAQ

### What is Fine Tuning in simple terms?

Fine tuning adapts a pretrained model to a narrower task or style using additional examples.

### Why does Fine Tuning matter for teams using AI?

Fine-tuning can adapt behavior or task performance, but it is not the default fix for missing current knowledge. Teams should compare prompting, retrieval, and fine-tuning on the same evaluation set and account for training data quality and maintenance.

### What is a practical example of Fine Tuning?

A company fine-tunes a smaller model on reviewed classification examples after prompt-only performance plateaus, while policy facts remain in a retrieved knowledge source.


Source: https://www.luffy.so/ai-glossary/fine-tuning

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