API Reference

Fine Tuning

Jobs

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Create fine-tuning job

fine_tuning.jobs.create(**kwargs) -> FineTuningJob { id, created_at, error, 16 more }

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

ParametersExpand Collapse

model: String | :"babbage-002" | :"davinci-002" | :"gpt-3.5-turbo" | :"gpt-4o-mini"

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, completions format, or if the fine-tuning method uses the preference format.

See the fine-tuning guide for more details.

Deprecatedhyperparameters: Hyperparameters{ batch_size, learning_rate_multiplier, n_epochs}

The hyperparameters used for the fine-tuning job. This value is now deprecated in favor of method, and should be passed in under the method parameter.

integrations: Array[Integration{ type, wandb}]

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

metadata: Metadata

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

method_: Method{ type, dpo, reinforcement, supervised}

The method used for fine-tuning.

seed: Integer

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.

minimum0

maximum2147483647

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.

minLength1

maxLength64

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.

ReturnsExpand Collapse

class FineTuningJob { id, created_at, error, 16 more }

The fine_tuning.job object represents a fine-tuning job that has been created through the API.

id: String

The object identifier, which can be referenced in the API endpoints.

created_at: Integer

The Unix timestamp (in seconds) for when the fine-tuning job was created.

formatunixtime

error: Error{ code, message, param}

For fine-tuning jobs that have failed, this will contain more information on the cause of the failure.

fine_tuned_model: String

The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.

finished_at: Integer

The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.

formatunixtime

hyperparameters: Hyperparameters{ batch_size, learning_rate_multiplier, n_epochs}

The hyperparameters used for the fine-tuning job. This value will only be returned when running supervised jobs.

model: String

The base model that is being fine-tuned.

object: :"fine_tuning.job"

The object type, which is always “fine_tuning.job”.

organization_id: String

The organization that owns the fine-tuning job.

result_files: Array[String]

The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the Files API.

seed: Integer

The seed used for the fine-tuning job.

status: :validating_files | :queued | :running | 3 more

The current status of the fine-tuning job, which can be either validating_files, queued, running, succeeded, failed, or cancelled.

trained_tokens: Integer

The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running.

training_file: String

The file ID used for training. You can retrieve the training data with the Files API.

validation_file: String

The file ID used for validation. You can retrieve the validation results with the Files API.

estimated_finish: Integer

The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running.

formatunixtime

integrations: Array[FineTuningJobWandbIntegrationObject { type, wandb } ]

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

metadata: Metadata

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

method_: Method{ type, dpo, reinforcement, supervised}

The method used for fine-tuning.

Create fine-tuning job

Ruby

HTTP

Python

TypeScript

Go

Ruby

Java

CLI Tool

require "openai"

openai = OpenAI::Client.new(api_key: "My API Key")

fine_tuning_job = openai.fine_tuning.jobs.create(model: :"gpt-4o-mini", training_file: "file-abc123")

puts(fine_tuning_job)

{
  "object": "fine_tuning.job",
  "id": "ftjob-abc123",
  "model": "gpt-4o-mini-2024-07-18",
  "created_at": 1721764800,
  "fine_tuned_model": null,
  "organization_id": "org-123",
  "result_files": [],
  "status": "queued",
  "validation_file": null,
  "training_file": "file-abc123",
  "method": {
    "type": "supervised",
    "supervised": {
      "hyperparameters": {
        "batch_size": "auto",
        "learning_rate_multiplier": "auto",
        "n_epochs": "auto",
      }
    }
  },
  "metadata": null
}

Returns Examples

{
  "object": "fine_tuning.job",
  "id": "ftjob-abc123",
  "model": "gpt-4o-mini-2024-07-18",
  "created_at": 1721764800,
  "fine_tuned_model": null,
  "organization_id": "org-123",
  "result_files": [],
  "status": "queued",
  "validation_file": null,
  "training_file": "file-abc123",
  "method": {
    "type": "supervised",
    "supervised": {
      "hyperparameters": {
        "batch_size": "auto",
        "learning_rate_multiplier": "auto",
        "n_epochs": "auto",
      }
    }
  },
  "metadata": null
}