Status of the training job.

interface TrainingResourceEntity {
    auto_update_model?: boolean;
    custom?: WatsonXAI.JsonObject;
    model_id: string;
    prompt_tuning?: WatsonXAI.PromptTuning;
    results_reference: WatsonXAI.ObjectLocation;
    status: WatsonXAI.TrainingStatus;
    training_data_references?: WatsonXAI.DataConnectionReference[];
}

Properties

auto_update_model?: boolean

If set to true then the result of the training, if successful, will be uploaded to the repository as a model.

User defined properties specified as key-value pairs.

model_id: string

Trained model id

prompt_tuning?: WatsonXAI.PromptTuning

Properties to control the prompt tuning.

results_reference: WatsonXAI.ObjectLocation

The training results. Normally this is specified as type=container which means that it is stored in the space or project. Note that the training will add some fields that point to the training status, the model request and the assets.

The model_request_path is the request body that should be used when creating the trained model in the API, if this model is to be deployed. If auto_update_model was set to true then this file is not needed.

Status of the training job.

training_data_references?: WatsonXAI.DataConnectionReference[]

Training datasets.