SageMaker Hyperparameter Tuning Job

This table represents the SageMaker Hyperparameter Tuning Job resource from Amazon Web Services.

aws.sagemaker_hyperparametertuningjob

Fields

TitleIDTypeData TypeDescription
_keycorestring
account_idcorestring
autotunecorejsonA flag to indicate if autotune is enabled for the hyperparameter tuning job.
best_training_jobcorejsonA <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TrainingJobSummary.html">TrainingJobSummary</a> object that describes the training job that completed with the best current <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobObjective.html">HyperParameterTuningJobObjective</a>.
consumed_resourcescorejson
creation_timecoretimestampThe date and time that the tuning job started.
failure_reasoncorestringIf the tuning job failed, the reason it failed.
hyper_parameter_tuning_end_timecoretimestampThe date and time that the tuning job ended.
hyper_parameter_tuning_job_arncorestringThe Amazon Resource Name (ARN) of the tuning job.
hyper_parameter_tuning_job_configcorejsonThe <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobConfig.html">HyperParameterTuningJobConfig</a> object that specifies the configuration of the tuning job.
hyper_parameter_tuning_job_namecorestringThe name of the hyperparameter tuning job.
hyper_parameter_tuning_job_statuscorestringThe status of the tuning job.
last_modified_timecoretimestampThe date and time that the status of the tuning job was modified.
objective_status_counterscorejsonThe <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ObjectiveStatusCounters.html">ObjectiveStatusCounters</a> object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.
overall_best_training_jobcorejsonIf the hyperparameter tuning job is an warm start tuning job with a <code>WarmStartType</code> of <code>IDENTICAL_DATA_AND_ALGORITHM</code>, this is the <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TrainingJobSummary.html">TrainingJobSummary</a> for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.
tagscorehstore
training_job_definitioncorejsonThe <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html">HyperParameterTrainingJobDefinition</a> object that specifies the definition of the training jobs that this tuning job launches.
training_job_definitionscorejsonA list of the <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html">HyperParameterTrainingJobDefinition</a> objects launched for this tuning job.
training_job_status_counterscorejsonThe <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TrainingJobStatusCounters.html">TrainingJobStatusCounters</a> object that specifies the number of training jobs, categorized by status, that this tuning job launched.
tuning_job_completion_detailscorejsonTuning job completion information returned as the response from a hyperparameter tuning job. This information tells if your tuning job has or has not converged. It also includes the number of training jobs that have not improved model performance as evaluated against the objective function.
warm_start_configcorejsonThe configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.