# What is Supervised Fine-Tuning?

*Artificial Intelligence · Last updated: October 23, 2026*

> SFT

It is the process of adapting a pre-trained artificial intelligence model to a specific task using labeled data pairs.

## Overview

Supervised Fine-Tuning enables foundation models, which have acquired general language skills through large datasets, to be directed toward a specific area of expertise. In this process, direct sample data prepared in the form of questions and ideal responses are presented to the model. The model learns how to generate correct responses to given instructions by analyzing these labeled data pairs.

***Analogy:** It is similar to a doctor with general medical training specializing in a specific disease type by reviewing documented cases.*

## How it works

The model's weights are updated by small margins based on the input and output patterns in the prepared dataset. By calculating the error rate, the model's responses are made to approach the target responses. This process helps align the model with the desired format without experiencing overfitting.

## Where it is used

It is used to ensure customer service bots respond appropriately to internal company documents and to make coding assistants produce output according to specific standards.

## Commonly confused with

It can be confused with the general concept of Fine-Tuning. While Fine-Tuning is a general adaptation umbrella, Supervised Fine-Tuning represents the specific stage conducted with labeled instruction and response pairs.

## Questions and answers

**How much data is needed for Supervised Fine-Tuning?**

Depending on the complexity of the task you are developing, generally between a few hundred and a few thousand quality data pairs are sufficient.

**Does the SFT process make the model forget its general capabilities?**

In misconfigured or overly prolonged training processes, the model may carry the risk of losing its general knowledge base.

## Related terms

- [Fine-tuning](https://trescout.com/en/dictionary/fine-tuning/)
- [Post-training](https://trescout.com/en/dictionary/post-training/)
- [RLHF](https://trescout.com/en/dictionary/rlhf/)
- [Foundation Model](https://trescout.com/en/dictionary/foundation-model/)

This explanation was written in plain language for TreScout with AI and **machine-translated** from the Turkish original · the Turkish version prevails. If something looks wrong or missing, write to [hello@trescout.com](mailto:hello@trescout.com). [Read in Turkish →](https://trescout.com/dictionary/supervised-fine-tuning/)

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Source: TreScout Dictionary · https://trescout.com/en/dictionary/supervised-fine-tuning/