Amazon SageMaker
Developer Guide

HyperParameterTuningJobConfig

Configures a hyperparameter tuning job.

Contents

HyperParameterTuningJobObjective

The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.

Type: HyperParameterTuningJobObjective object

Required: No

ParameterRanges

The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.

Type: ParameterRanges object

Required: No

ResourceLimits

The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs for this tuning job.

Type: ResourceLimits object

Required: Yes

Strategy

Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. To use the Bayesian search strategy, set this to Bayesian. To randomly search, set it to Random. For information about search strategies, see How Hyperparameter Tuning Works.

Type: String

Valid Values: Bayesian | Random

Required: Yes

TrainingJobEarlyStoppingType

Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. This can be one of the following values (the default value is OFF):

OFF

Training jobs launched by the hyperparameter tuning job do not use early stopping.

AUTO

Amazon SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.

Type: String

Valid Values: Off | Auto

Required: No

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following:

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