Skip to content

Latest commit

 

History

History
557 lines (483 loc) · 15.5 KB

openai-finetuning-guide.md

File metadata and controls

557 lines (483 loc) · 15.5 KB
Raw

Fine-tuning

Manage fine-tuning jobs to tailor a model to your specific training data.

Create Fine-tuning Job

POST https://api.openai.com/v1/fine_tuning/jobs

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

Request Body

  • model: string (Required) The name of the model to fine-tune. You can select one of the supported models.
  • training_file: string (Required) The ID of an uploaded file that contains training data. 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: object (Optional) The hyperparameters used for the fine-tuning job.
  • suffix: string or null (Optional) Defaults to null. A string of up to 18 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-3.5-turbo:openai:custom-model-name:7p4lURel.
  • validation_file: string or null (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.
  • integrations: array or null (Optional) A list of integrations to enable for your fine-tuning job.
  • seed: integer or null (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.

Returns

A fine-tuning.job object.

Example Request

curl https://api.openai.com/v1/fine_tuning/jobs \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "training_file": "file-abc123",
    "validation_file": "file-abc123",
    "model": "gpt-3.5-turbo",
    "integrations": [
      {
        "type": "wandb",
        "wandb": {
          "project": "my-wandb-project",
          "name": "ft-run-display-name",
          "tags": [
            "first-experiment", "v2"
          ]
        }
      }
    ]
  }'

Response

{
  "object": "fine_tuning.job",
  "id": "ftjob-abc123",
  "model": "gpt-3.5-turbo-0125",
  "created_at": 1614807352,
  "fine_tuned_model": null,
  "organization_id": "org-123",
  "result_files": [],
  "status": "queued",
  "validation_file": "file-abc123",
  "training_file": "file-abc123",
  "integrations": [
    {
      "type": "wandb",
      "wandb": {
        "project": "my-wandb-project",
        "entity": null,
        "run_id": "ftjob-abc123"
      }
    }
  ]
}

List Fine-tuning Jobs

GET https://api.openai.com/v1/fine_tuning/jobs

List your organization's fine-tuning jobs.

Query Parameters

  • after: string (Optional) Identifier for the last job from the previous pagination request.
  • limit: integer (Optional) Defaults to 20. Number of fine-tuning jobs to retrieve.

Returns

A list of paginated fine-tuning job objects.

Example Request

import OpenAI from "openai";

const openai = new OpenAI();

async function main() {
  const list = await openai.fineTuning.jobs.list();

  for await (const fineTune of list) {
    console.log(fineTune);
  }
}

main();

Response

{
  "object": "list",
  "data": [
    {
      "object": "fine_tuning.job.event",
      "id": "ft-event-TjX0lMfOniCZX64t9PUQT5hn",
      "created_at": 1689813489,
      "level": "warn",
      "message": "Fine tuning process stopping due to job cancellation",
      "data": null,
      "type": "message"
    },
    { ... },
    { ... }
  ],
  "has_more": true
}

List Fine-tuning Events

GET https://api.openai.com/v1/fine_tuning/jobs/{fine_tuning_job_id}/events

Get status updates for a fine-tuning job.

Path Parameters

  • fine_tuning_job_id: string (Required) The ID of the fine-tuning job to get events for.

Query Parameters

  • after: string (Optional) Identifier for the last event from the previous pagination request.
  • limit: integer (Optional) Defaults to 20. Number of events to retrieve.

Returns

A list of fine-tuning event objects.

Example Request

import OpenAI from "openai";

const openai = new OpenAI();

async function main() {
  const list = await openai.fineTuning.list_events(id="ftjob-abc123", limit=2);

  for await (const fineTune of list) {
    console.log(fineTune);
  }
}

main();

Response

{
  "object": "list",
  "data": [
    {
      "object": "fine_tuning.job.event",
      "id": "ft-event-ddTJfwuMVpfLXseO0Am0Gqjm",
      "created_at": 1692407401,
      "level": "info",
      "message": "Fine tuning job successfully completed",
      "data": null,
      "type": "message"
    },
    {
      "object": "fine_tuning.job.event",
      "id": "ft-event-tyiGuB72evQncpH87xe505Sv",
      "created_at": 1692407400,
      "level": "info",
      "message": "New fine-tuned model created: ft:gpt-3.5-turbo:openai::7p4lURel",
      "data": null,
      "type": "message"
    }
  ],
  "has_more": true
}

List Fine-tuning Checkpoints

GET https://api.openai.com/v1/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints

List checkpoints for a fine-tuning job.

Path Parameters

  • fine_tuning_job_id: string (Required) The ID of the fine-tuning job to get checkpoints for.

Query Parameters

  • after: string (Optional) Identifier for the last checkpoint ID from the previous pagination request.
  • limit: integer (Optional) Defaults to 10. Number of checkpoints to retrieve.

Returns

A list of fine-tuning checkpoint objects for a fine-tuning job.

Example Request

curl https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/checkpoints \
  -H "Authorization: Bearer $OPENAI_API_KEY"

Response

{
  "object": "list",
  "data": [
    {
      "object": "fine_tuning.job.checkpoint",
      "id": "ftckpt_zc4Q7MP6XxulcVzj4MZdwsAB",
      "created_at": 1519129973,
      "fine_tuned_model_checkpoint": "ft:gpt-3.5-turbo-0125:my-org:custom-suffix:96olL566:ckpt-step-2000",
      "metrics": {
        "full_valid_loss": 0.134,
        "full_valid_mean_token_accuracy": 0.874
      },
      "fine_tuning_job_id": "ftjob-abc123",
      "step_number": 2000
    },
    {
      "object": "fine_tuning.job.checkpoint",
      "id": "ftckpt_enQCFmOTGj3syEpYVhBRLTSy",
      "created_at": 1519129833,
      "fine_tuned_model_checkpoint": "ft:gpt-3.5-turbo-0125:my-org:custom-suffix:7q8mpxmy:ckpt-step-1000

",
      "metrics": {
        "full_valid_loss": 0.167,
        "full_valid_mean_token_accuracy": 0.781
      },
      "fine_tuning_job_id": "ftjob-abc123",
      "step_number": 1000
    }
  ],
  "first_id": "ftckpt_zc4Q7MP6XxulcVzj4MZdwsAB",
  "last_id": "ftckpt_enQCFmOTGj3syEpYVhBRLTSy",
  "has_more": true
}

Retrieve Fine-tuning Job

GET https://api.openai.com/v1/fine_tuning/jobs/{fine_tuning_job_id}

Get info about a fine-tuning job.

Learn more about fine-tuning

Path Parameters

  • fine_tuning_job_id: string (Required) The ID of the fine-tuning job.

Returns

The fine-tuning object with the given ID.

Example Request

import OpenAI from "openai";

const openai = new OpenAI();

async function main() {
  const fineTune = await openai.fineTuning.jobs.retrieve("ftjob-abc123");

  console.log(fineTune);
}

main();

Response

{
  "object": "fine_tuning.job",
  "id": "ftjob-abc123",
  "model": "davinci-002",
  "created_at": 1692661014,
  "finished_at": 1692661190,
  "fine_tuned_model": "ft:davinci-002:my-org:custom_suffix:7q8mpxmy",
  "organization_id": "org-123",
  "result_files": [
      "file-abc123"
  ],
  "status": "succeeded",
  "validation_file": null,
  "training_file": "file-abc123",
  "hyperparameters": {
      "n_epochs": 4,
      "batch_size": 1,
      "learning_rate_multiplier": 1.0
  },
  "trained_tokens": 5768,
  "integrations": [],
  "seed": 0,
  "estimated_finish": 0
}

Cancel Fine-tuning

POST https://api.openai.com/v1/fine_tuning/jobs/{fine_tuning_job_id}/cancel

Immediately cancel a fine-tune job.

Path Parameters

  • fine_tuning_job_id: string (Required) The ID of the fine-tuning job to cancel.

Returns

The cancelled fine-tuning object.

Example Request

import OpenAI from "openai";

const openai = new OpenAI();

async function main() {
  const fineTune = await openai.fineTuning.jobs.cancel("ftjob-abc123");

  console.log(fineTune);
}

main();

Response

{
  "object": "fine_tuning.job",
  "id": "ftjob-abc123",
  "model": "gpt-3.5-turbo-0125",
  "created_at": 1689376978,
  "fine_tuned_model": null,
  "organization_id": "org-123",
  "result_files": [],
  "hyperparameters": {
    "n_epochs": "auto"
  },
  "status": "cancelled",
  "validation_file": "file-abc123",
  "training_file": "file-abc123"
}

Training Format for Chat Models

The per-line training example of a fine-tuning input file for chat models.

  • messages: array
  • tools: array A list of tools the model may generate JSON inputs for.
  • parallel_tool_calls: boolean Whether to enable parallel function calling during tool use.
  • functions: array (Deprecated) A list of functions the model may generate JSON inputs for.

Example

{
  "messages": [
    { "role": "user", "content": "What is the weather in San Francisco?" },
    {
      "role": "assistant",
      "tool_calls": [
        {
          "id": "call_id",
          "type": "function",
          "function": {
            "name": "get_current_weather",
            "arguments": "{\"location\": \"San Francisco, USA\", \"format\": \"celsius\"}"
          }
        }
      ]
    }
  ],
  "parallel_tool_calls": false,
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_current_weather",
        "description": "Get the current weather",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {
                "type": "string",
                "description": "The city and country, eg. San Francisco, USA"
            },
            "format": { "type": "string", "enum": ["celsius", "fahrenheit"] }
          },
          "required": ["location", "format"]
        }
      }
    }
  ]
}

Training Format for Completions Models

The per-line training example of a fine-tuning input file for completions models.

  • prompt: string The input prompt for this training example.
  • completion: string The desired completion for this training example.

Example

{
  "prompt": "What is the answer to 2+2",
  "completion": "4"
}

The Fine-tuning Job Object

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.
  • error: object or null For fine-tuning jobs that have failed, this will contain more information on the cause of the failure.
  • fine_tuned_model: string or null 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 or null 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 The hyperparameters used for the fine-tuning job. See the fine-tuning guide for more details.
  • model: string The base model that is being fine-tuned.
  • object: string The object type, which is always fine_tuning.job.
  • organization_id: string The organization that owns the fine-tuning job.
  • result_files: array The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the Files API.
  • status: string The current status of the fine-tuning job, which can be either validating_files, queued, running, succeeded, failed, or cancelled.
  • trained_tokens: integer or null 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 or null The file ID used for validation. You can retrieve the validation results with the Files API.
  • integrations: array or null A list of integrations to enable for this fine-tuning job.
  • seed: integer The seed used for the fine-tuning job.
  • estimated_finish: integer or null 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.

Example

{
  "object": "fine_tuning.job",
  "id": "ftjob-abc123",
  "model": "davinci-002",
  "created_at": 1692661014,
  "finished_at": 1692661190,
  "fine_tuned_model": "ft:davinci-002:my-org:custom_suffix:7q8mpxmy",
  "organization_id": "org-123",
  "result_files": [
      "file-abc123"
  ],
  "status": "succeeded",
  "validation_file": null,
  "training_file": "file-abc123",
  "hyperparameters": {
      "n_epochs": 4,
      "batch_size": 1,
      "learning_rate_multiplier": 1.0
  },
  "trained_tokens": 5768,
  "integrations": [],
  "seed": 0,
  "estimated_finish": 0
}

The Fine-tuning Job Event Object

The fine_tuning.job.event object represents an event during a fine-tuning job.

  • id: string
  • created_at: integer
  • level: string
  • **

message**: string

  • object: string

Example

{
  "object": "fine_tuning.job.event",
  "id": "ftevent-abc123",
  "created_at": 1677610602,
  "level": "info",
  "message": "Created fine-tuning job"
}

The Fine-tuning Job Checkpoint Object

The fine_tuning.job.checkpoint object represents a model checkpoint for a fine-tuning job that is ready to use.

  • id: string The checkpoint identifier, which can be referenced in the API endpoints.
  • created_at: integer The Unix timestamp (in seconds) for when the checkpoint was created.
  • fine_tuned_model_checkpoint: string The name of the fine-tuned checkpoint model that is created.
  • step_number: integer The step number that the checkpoint was created at.
  • metrics: object Metrics at the step number during the fine-tuning job.
  • fine_tuning_job_id: string The name of the fine-tuning job that this checkpoint was created from.
  • object: string The object type, which is always fine_tuning.job.checkpoint.

Example

{
  "object": "fine_tuning.job.checkpoint",
  "id": "ftckpt_zc4Q7MP6XxulcVzj4MZdwsAB",
  "created_at": 1519129973,
  "fine_tuned_model_checkpoint": "ft:gpt-3.5-turbo-0125:my-org:custom-suffix:96olL566:ckpt-step-2000",
  "metrics": {
    "full_valid_loss": 0.134,
    "full_valid_mean_token_accuracy": 0.874
  },
  "fine_tuning_job_id": "ftjob-abc123",
  "step_number": 2000
}