Training a Git Model Version - Teradata Vantage

ClearScape Analytics ModelOps User Guide

Teradata Vantage
Release Number
April 2023
English (United States)
Last Update
  1. Select the
    of a Git model in the models list.
  2. Select Train Model.
  3. In the Basic tab, set the properties:
    Property Description
    Model Specifies the model name in read-only format.
    Dataset Template Specifies the required dataset template.
    Dataset Specifies the dataset to be used to train the model.
    Hyper parameters Allows you to set the training variables manually with a pre-determined value before starting the training job.
  4. In the Advanced tab, set the properties:
    Property Description
    Engine Specifies the engine to train the model in read-only format.
    Docker Image Specifies the docker version to be used to train the model.
    Resource Template Allows you to use a predefined set of resources, including CPU and memory, which are the properties of the container created to run evaluation script in.

    Select S Standard, M Medium, L Large or Custom from the dropdown list.

    With Custom selection, there are three additional Properties:
    • Memory: Free text to specify memory resource.
    • CPU: Free text to specify container CPU resource.
    • GPU: Specifies the GPU resource for the container.
  5. Select Train Model.
    The Training in Progress page displays the model version training progress.

    The Logs tab shows the job logs and events for the selected job.

    Training a Git Model - Logs tab

    The Properties tab shows all properties related to the selected job such as jobId, datasetid, and hyperparameters include dataset properties.

    Training a Git Model - Properties tab
  6. Click the
    to close the sheet when the training progress completes.

    The List of model versions displays the following properties for each version.

    Property Description
    Trained Model ID Specifies the auto-generated trained model ID.
    Status Specifies the version status as Trained, Evaluated, Approved, Rejected, Deployed, Retired.
    Dataset Specifies the dataset used to train the version.
    Created By Shows the username who has created the version.
    Tags Displays the list of tags associated with the model version.
    Champion Shows whether the version is champion or not.