curl -X GET 'https://api.openai.com/v1/fine_tuning/jobs?after=example-after&limit=20&metadata=example-metadata' \
  -H "Authorization: Bearer $OPENAI_API_KEY"

# GET /fine_tuning/jobs (OpenAI API)
Base URL: https://api.openai.com/v1
Auth: Authorization; OpenAI API key; required.
Last verified: 2026-10-20

> List fine-tuning jobs

## Critical Gotchas
* The Responses API is the primary interface for new text and tool workflows; Chat Completions remains a separate compatibility API.
* Audio transcription uploads use multipart form data rather than a JSON request body.

## cURL
curl -X GET 'https://api.openai.com/v1/fine_tuning/jobs?after=example-after&limit=20&metadata=example-metadata' \
  -H "Authorization: Bearer $OPENAI_API_KEY"

## Parameters
| Name | In | Type | Required | Description |
| :--- | :--- | :--- | :--- | :--- |
| after | query | string | No | Identifier for the last job from the previous pagination request. |
| limit | query | integer | No | Number of fine-tuning jobs to retrieve. |
| metadata | query | object | No | Optional metadata filter. To filter, use the syntax `metadata[k]=v`. Omitting... |

## Response example
{"data":[{}],"has_more":true}

---
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GET

GET /fine_tuning/jobs — OpenAI API

OpenAI API key (required); https://api.openai.com/v1

OpenAI API

List fine-tuning jobs

Base URL: https://api.openai.com/v1
Auth: Authorization: Bearer <OPENAI_API_KEY>
Last verified: 2026-10-20 · upstream hash matched

Actions Try in browser→

Agents: curl -H "Accept: text/markdown" this URL
→ 212 tokens · Vary: Accept

Critical gotchas

The Responses API is the primary interface for new text and tool workflows; Chat Completions remains a separate compatibility API.

Audio transcription uploads use multipart form data rather than a JSON request body.

cURL

curl -X GET 'https://api.openai.com/v1/fine_tuning/jobs?after=example-after&limit=20&metadata=example-metadata' \  -H "Authorization: Bearer $OPENAI_API_KEY"

Parameters

Name	In	Type	Required	Description
after	query	string	No	Identifier for the last job from the previous pagination request.
limit	query	integer	No	Number of fine-tuning jobs to retrieve.
metadata	query	object	No	Optional metadata filter. To filter, use the syntax `metadata[k]=v`. Omitting the parameter or passing an empty object applies no metadata filter. An empty value, such as `metadata[k]=`, filters for that key with an empty string value. To select jobs with null metadata, send the literal query string `metadata=null`. Nullable caller types do not specify how a client serializes null for a deep-object parameter. Use a raw query parameter if the client omits null. Do not combine the two query forms.

Response 200 OK

{
  "data": [
    {
      "id": "string",
      "created_at": 0,
      "error": {
        "code": "string",
        "message": "string",
        "param": "string"
      },
      "fine_tuned_model": "string",
      "finished_at": 0,
      "hyperparameters": {
        "batch_size": "auto",
        "learning_rate_multiplier": "auto",
        "n_epochs": "auto"
      },
      "model": "string",
      "object": "fine_tuning.job",
      "organization_id": "string",
      "result_files": [
        "file-abc123"
      ],
      "status": "validating_files",
      "trained_tokens": 0,
      "training_file": "string",
      "validation_file": "string",
      "integrations": [
        {
          "type": "wandb",
          "wandb": {
            "project": "[recursive or deeply nested schema]",
            "name": "[recursive or deeply nested schema]",
            "entity": "[recursive or deeply nested schema]",
            "tags": "[recursive or deeply nested schema]"
          }
        }
      ],
      "seed": 0,
      "estimated_finish": 0,
      "method": {
        "type": "supervised",
        "supervised": {
          "hyperparameters": {
            "batch_size": "[recursive or deeply nested schema]",
            "learning_rate_multiplier": "[recursive or deeply nested schema]",
            "n_epochs": "[recursive or deeply nested schema]"
          }
        },
        "dpo": {
          "hyperparameters": {
            "beta": "[recursive or deeply nested schema]",
            "batch_size": "[recursive or deeply nested schema]",
            "learning_rate_multiplier": "[recursive or deeply nested schema]",
            "n_epochs": "[recursive or deeply nested schema]"
          }
        },
        "reinforcement": {
          "grader": {
            "type": "[recursive or deeply nested schema]",
            "name": "[recursive or deeply nested schema]",
            "input": "[recursive or deeply nested schema]",
            "reference": "[recursive or deeply nested schema]",
            "operation": "[recursive or deeply nested schema]"
          },
          "hyperparameters": {
            "batch_size": "[recursive or deeply nested schema]",
            "learning_rate_multiplier": "[recursive or deeply nested schema]",
            "n_epochs": "[recursive or deeply nested schema]",
            "reasoning_effort": "[recursive or deeply nested schema]",
            "compute_multiplier": "[recursive or deeply nested schema]",
            "eval_interval": "[recursive or deeply nested schema]",
            "eval_samples": "[recursive or deeply nested schema]"
          }
        }
      },
      "metadata": {}
    }
  ],
  "has_more": true,
  "object": "list"
}

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