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Class: Aws::SageMaker::Types::HyperParameterTuningJobSummary
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::HyperParameterTuningJobSummary
- Defined in:
- (unknown)
Overview
Provides summary information about a hyperparameter tuning job.
Instance Attribute Summary collapse
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#creation_time ⇒ Time
The date and time that the tuning job was created.
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#hyper_parameter_tuning_end_time ⇒ Time
The date and time that the tuning job ended.
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#hyper_parameter_tuning_job_arn ⇒ String
The Amazon Resource Name (ARN) of the tuning job.
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#hyper_parameter_tuning_job_name ⇒ String
The name of the tuning job.
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#hyper_parameter_tuning_job_status ⇒ String
The status of the tuning job.
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#last_modified_time ⇒ Time
The date and time that the tuning job was modified.
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#objective_status_counters ⇒ Types::ObjectiveStatusCounters
The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.
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#resource_limits ⇒ Types::ResourceLimits
The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.
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#strategy ⇒ String
Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to use for each iteration.
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#training_job_status_counters ⇒ Types::TrainingJobStatusCounters
The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.
Instance Attribute Details
#creation_time ⇒ Time
The date and time that the tuning job was created.
#hyper_parameter_tuning_end_time ⇒ Time
The date and time that the tuning job ended.
#hyper_parameter_tuning_job_arn ⇒ String
The Amazon Resource Name (ARN) of the tuning job.
#hyper_parameter_tuning_job_name ⇒ String
The name of the tuning job.
#hyper_parameter_tuning_job_status ⇒ String
The status of the tuning job.
Possible values:
- Completed
- InProgress
- Failed
- Stopped
- Stopping
#last_modified_time ⇒ Time
The date and time that the tuning job was modified.
#objective_status_counters ⇒ Types::ObjectiveStatusCounters
The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.
#resource_limits ⇒ Types::ResourceLimits
The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.
#strategy ⇒ String
Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to use for each iteration. Currently, the only valid value is Bayesian.
Possible values:
- Bayesian
- Random
#training_job_status_counters ⇒ Types::TrainingJobStatusCounters
The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.