Create fine-tuning job

$ openai fine-tuning:jobs create

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 or "babbage-002" or "davinci-002" or "gpt-3.5-turbo" or "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.

Deprecated--hyperparameters: optional object { 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.

--integration: optional array of object { type, wandb }

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

--metadata: optional map[string]

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: optional object { type, dpo, reinforcement, supervised }

The method used for fine-tuning.

--seed: optional 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: optional 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: optional 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

fine_tuning_job: object { 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: number

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

error: object { code, message, param }

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

View schema details

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: number

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.

hyperparameters: object { 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.

View schema details

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 of string

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

seed: number

The seed used for the fine-tuning job.

status: "validating_files" or "queued" or "running" or 3 more

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

View schema details

trained_tokens: number

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: optional number

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.

integrations: optional array of FineTuningJobWandbIntegrationObject { type, wandb }

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

View schema details

metadata: optional map[string]

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

method: optional object { type, dpo, reinforcement, supervised }

The method used for fine-tuning.

View schema details