API Reference

Fine Tuning

Jobs

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Create fine-tuning job

client.FineTuning.Jobs.New(ctx, body) (*FineTuningJob, error)

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

body FineTuningJobNewParams

Model param.Field[FineTuningJobNewParamsModel]

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

TrainingFile param.Field[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 param.Field[FineTuningJobNewParamsHyperparameters]Optional

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 param.Field[[]FineTuningJobNewParamsIntegration]Optional

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

Metadata param.Field[Metadata]Optional

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 param.Field[FineTuningJobNewParamsMethod]Optional

The method used for fine-tuning.

Seed param.Field[int64]Optional

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 param.Field[string]Optional

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

ValidationFile param.Field[string]Optional

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

type FineTuningJob struct{…}

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.

CreatedAt int64

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

formatunixtime

Error FineTuningJobError

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

FineTunedModel 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.

FinishedAt int64

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 FineTuningJobHyperparameters

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 FineTuningJob

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

OrganizationID string

The organization that owns the fine-tuning job.

ResultFiles []string

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

Seed int64

The seed used for the fine-tuning job.

Status FineTuningJobStatus

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

TrainedTokens int64

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.

TrainingFile string

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

ValidationFile string

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

EstimatedFinish int64Optional

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 []FineTuningJobWandbIntegrationObjectOptional

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

Metadata MetadataOptional

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 FineTuningJobMethodOptional

The method used for fine-tuning.

Create fine-tuning job

Go

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Python

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Java

CLI Tool

package main

import (
  "context"
  "fmt"

  "github.com/openai/openai-go"
  "github.com/openai/openai-go/option"
)

func main() {
  client := openai.NewClient(
    option.WithAPIKey("My API Key"),
  )
  fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
    Model: openai.FineTuningJobNewParamsModelGPT4oMini,
    TrainingFile: "file-abc123",
  })
  if err != nil {
    panic(err.Error())
  }
  fmt.Printf("%+v\n", fineTuningJob.ID)
}

{
  "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
}