OpenAI API | Fine Tuning › Jobs › Create Fine Tuning Job

OpenAI API

Fine Tuning

fine_tuning

Fine Tuning

Jobs

fine_tuning.jobs

Methods

Cancel Fine Tuning ->

FineTuningJob

post/fine_tuning/jobs/{fine_tuning_job_id}/cancel

Immediately cancel a fine-tune job.

Create Fine Tuning Job ->

FineTuningJob

post/fine_tuning/jobs

Creates a fine-tuning job which begins the process of creating a new model from a given dataset.

Response includes details of the enqueued job including job status and the name of the fine-tuned models once complete.

Learn more about fine-tuning

Security

Bearer Auth

Example: Authorization: Bearer My API Key

Body parameters

model: string | "babbage-002" | "davinci-002" | "gpt-3.5-turbo" | 1 more...

The name of the model to fine-tune. You can select one of the supported models.

training_file: string

The ID of an uploaded file that contains training data.

See upload file for how to upload a file.

Your dataset must be formatted as a JSONL file. Additionally, you must upload your file with the purpose fine-tune.

The contents of the file should differ depending on if the model uses the chat or completions format.

See the fine-tuning guide for more details.

hyperparameters?: { batch_size, learning_rate_multiplier, n_epochs }

The hyperparameters used for the fine-tuning job.

integrations?: Array<{ type, wandb }>

A list of integrations to enable for your fine-tuning job.

seed?: number

The seed controls the reproducibility of the job. Passing in the same seed and job parameters should produce the same results, but may differ in rare cases. If a seed is not specified, one will be generated for you.

suffix?: string

A string of up to 64 characters that will be added to your fine-tuned model name.

For example, a suffix of "custom-model-name" would produce a model name like ft:gpt-4o-mini:openai:custom-model-name:7p4lURel.

validation_file?: string

The ID of an uploaded file that contains validation data.

If you provide this file, the data is used to generate validation metrics periodically during fine-tuning. These metrics can be viewed in the fine-tuning results file. The same data should not be present in both train and validation files.

Your dataset must be formatted as a JSONL file. You must upload your file with the purpose fine-tune.

See the fine-tuning guide for more details.

Response fields

FineTuningJob

Request example

curl https://api.openai.com/v1/fine_tuning/jobs \
    -H 'Content-Type: application/json' \
    -H "Authorization: Bearer $OPENAI_API_KEY" \
    -d '{
      "model": "gpt-4o-mini",
      "training_file": "file-abc123",
      "seed": 42,
      "validation_file": "file-abc123"
    }'

200Example

{
  "id": "id",
  "created_at": 0,
  "error": {
    "code": "code",
    "message": "message",
    "param": "param"
  },
  "fine_tuned_model": "fine_tuned_model",
  "finished_at": 0,
  "hyperparameters": {
    "n_epochs": "auto"
  },
  "model": "model",
  "object": "fine_tuning.job",
  "organization_id": "organization_id",
  "result_files": [
    "file-abc123"
  ],
  "seed": 0,
  "status": "validating_files",
  "trained_tokens": 0,
  "training_file": "training_file",
  "validation_file": "validation_file",
  "estimated_finish": 0,
  "integrations": [
    {
      "type": "wandb",
      "wandb": {
        "project": "my-wandb-project",
        "entity": "entity",
        "name": "name",
        "tags": [
          "custom-tag"
        ]
      }
    }
  ]
}