openai · OpenAI Platform Docs

Supervised fine-tuning

A guide on the end-to-end process of supervised fine-tuning, covering dataset construction, example quality, data formatting in JSONL, and the workflow for creating and evaluating fine-tuning jobs.

Import to Prompt Buddy

Derived skill

Files assembled from official documentation

Viewing SKILL.md

Supervised fine-tuning

A guide on the end-to-end process of supervised fine-tuning, covering dataset construction, example quality, data formatting in JSONL, and the workflow for creating and evaluating fine-tuning jobs.

When To Use

Use when you need to customize a base model to follow specific styles, formats, or instruction-following patterns through a structured training dataset.

Reference Files

File	Contains	Use For
`SKILL.md`	Entry point: scope, routing table, and workflow.	Start here.
`docs/supervised-fine-tuning-workflow-guide.md`	A guide explaining the concepts, dataset requirements, and best practices for supervised fine-tuning on the OpenAI platform.	Questions about a guide explaining the concepts, dataset requirements, and best practices for supervised fine-tuning on the OpenAI pl...

What This Skill Covers

Supervised fine-tuning (SFT) lets you train an OpenAI model with examples for your specific use case. The result is a customized model that more reliably pro...
Main sections: Overview, Build your dataset, Right number of examples, What makes a good example, Formatting your data.

Workflow

Open the most relevant file under docs/ for the exact documented workflow and wording.
Open schemas/ files for exact structured contracts.
Open examples/ files for concrete requests, commands, snippets, and manifests.
Do not add behavior or configuration that is not present in the attached source files.

Canonical source: https://developers.openai.com/api/docs/guides/supervised-fine-tuning.md