List Fine Tune Jobs

POST 
/api/2/auto_eval/fine_tune_job/list

List all fine-tune jobs with optional filters.

Request

application/json

Body

filters

object

query string

search query substring match for name and description

status string

Responses

200

Successful operation

application/json

Schema

Schema

jobs

object[]

required

Array [

id stringrequired

The ID of the fine tune job.

createdAt date-timerequired

updatedAt date-timerequired

name string

Name corresponding to the fine tuned model derived from this job

description string

status stringrequired

config

object

required

name string

Optional name for the job.

description string

Optional description for the job.

baselineModelId stringrequired

The ID for the model used as the starting point for training.

trainDatasetId stringrequired

The dataset to use for training, with splits baked in or to be derived dynamically

testDatasetId stringrequired

The dataset to use for an unbiased evaluation of the model

selectedColumns string[]required

result

object

required

Result of a Fine-Tuning Job.

progress

object[]

required

Array [

jobId stringrequired

epoch integerrequired

loss numberrequired

accuracy numberrequired

progress numberrequired

timestamp date-timerequired

]

trainedModelFile

object

The trained model, if it was created successfully.

id stringrequired

createdAt date-timerequired

updatedAt date-timerequired

modelId stringrequired

contentMd5Hash stringrequired

fileSizeBytes integerrequired

resultUrl string

Url to view the full results and progress (e.g. external W&B url)

]

totalCount integerrequired

Total count of fine tune jobs which can be listed with applicable filters, regardless of page size

Example (from schema)

{
  "jobs": [
    {
      "id": "string",
      "createdAt": "2024-07-29T15:51:28.071Z",
      "updatedAt": "2024-07-29T15:51:28.071Z",
      "name": "string",
      "description": "string",
      "status": "string",
      "config": {
        "name": "string",
        "description": "string",
        "baselineModelId": "string",
        "trainDatasetId": "string",
        "testDatasetId": "string",
        "selectedColumns": [
          "string"
        ]
      },
      "result": {
        "progress": [
          {
            "jobId": "string",
            "epoch": 0,
            "loss": 0,
            "accuracy": 0,
            "progress": 0,
            "timestamp": "2024-07-29T15:51:28.071Z"
          }
        ],
        "trainedModelFile": {
          "id": "string",
          "createdAt": "2024-07-29T15:51:28.071Z",
          "updatedAt": "2024-07-29T15:51:28.071Z",
          "modelId": "string",
          "contentMd5Hash": "string",
          "fileSizeBytes": 0
        },
        "resultUrl": "string"
      }
    }
  ],
  "totalCount": 0
}

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