> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mathfi.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# List training jobs

> List all training



## OpenAPI

````yaml api-reference/openapi.yaml GET /api/v1/training
openapi: 3.0.1
info:
  title: MathFi.ai API
  description: >
    The MathFi.ai REST API runs the two products end to end.


    **Feature Refinery** takes your labelled data and works out which columns

    actually carry the signal. It returns a reduced train and test pair, a

    per-column keep/remove decision, and the performance target the refined data

    reached.


    **Model Crucible** takes a dataset, trains every algorithm family against it

    at once, ranks the results on held-out data by fewest wrong decisions, and

    keeps the best three as versions of one model. You pick which one
    predictions

    run against.


    Everything is asynchronous: you create a thing, upload to a signed URL,
    start

    it, then poll until the state is terminal. Nothing streams and nothing
    blocks.
  contact:
    name: MathFi.ai
    url: https://mathfi.ai
    email: support@mathfi.ai
  license:
    name: MathFi.ai
    url: https://mathfi.ai
  version: 1.0.0
servers:
  - url: https://{tenant}-api.mathfi.ai
    description: >-
      Your tenant's API. Each customer has their own, so the host varies.
      Replace {tenant} with the name issued when your tenant was created.
    variables:
      tenant:
        default: your-tenant
        description: The tenant name issued to you.
security:
  - BearerAuth: []
tags:
  - name: Authentication
    description: Exchange credentials for a bearer token
  - name: Feature Refinery
    description: Reduce a dataset to the columns that earn their place
  - name: Datasets
    description: >-
      Prepare labelled data for training, from uploads or from a finished
      refinement
  - name: Training
    description: Run the Crucible against a dataset and choose the champion model
  - name: Models
    description: Trained models and their versions
  - name: Predictions
    description: Score unlabelled data against a champion model
paths:
  /api/v1/training:
    get:
      tags:
        - Training
      summary: List training jobs
      description: List all training
      operationId: listTrainingByUser
      parameters:
        - name: offset
          in: query
          required: true
          schema:
            minimum: 0
            type: integer
            format: int64
        - name: limit
          in: query
          required: true
          schema:
            minimum: 1
            type: integer
            format: int64
        - name: parentOnly
          in: query
          required: false
          schema:
            type: boolean
            default: false
      responses:
        '200':
          description: Training jobs successfully listed
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/TrainingJobList'
        '400':
          description: Invalid parameters passed
components:
  schemas:
    TrainingJobList:
      required:
        - limit
        - offset
        - total
        - trainingJobs
      type: object
      properties:
        trainingJobs:
          type: array
          items:
            $ref: '#/components/schemas/TrainingJobListItem'
        offset:
          type: integer
          format: int64
        nextOffset:
          type: integer
          format: int64
        limit:
          type: integer
          format: int64
        total:
          type: integer
          format: int64
    TrainingJobListItem:
      required:
        - scalingFactor
        - status
        - targetPerformance
        - trainingJobKey
      type: object
      properties:
        trainingJobKey:
          type: string
          format: uuid
        datasetKey:
          type: string
          format: uuid
        datasetName:
          type: string
        status:
          $ref: '#/components/schemas/TrainingJobStatus'
        scalingFactor:
          type: integer
          format: int32
        targetPerformance:
          type: number
          format: double
        modelKey:
          type: string
          format: uuid
        achievedPerformance:
          type: number
          format: double
        trainingPerformance:
          type: number
          format: double
        testPerformance:
          type: number
          format: double
        createdOn:
          type: string
    TrainingJobStatus:
      type: string
      description: >
        Status of training: 


        * `PENDING` - The training job has been created and is pending execution

        * `RUNNING` - The training job is currently executing and progressing

        * `COMPLETED` - The training job has completed execution successfully,
        reaching the target performance. A model has been generated. 

        * `TIMED_OUT` - The training job could not reach the target performance
        in the configured 

        * `CANCELLED` - The training job has been cancelled by the user 

        * `NOT_COMPLETED` - The training job has stalled without making progress
        in a specified timeframe

        * `FAILED` - The training job has failed due to an error
      enum:
        - PENDING
        - RUNNING
        - COMPLETED
        - TIMED_OUT
        - CANCELLED
        - FAILED
        - NOT_COMPLETED
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      bearerFormat: JWT

````