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TuningJobCompletionCriteria

Source code in docs_src/capo_sagemaker/types/tuning_job_completion_criteria.py 
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class TuningJobCompletionCriteria(TypedDict, closed=True):
    target_objective_metric_value: NotRequired[
        "capo_sagemaker.types.target_objective_metric_value.TargetObjectiveMetricValue"
    ]
    """<p>The value of the objective metric.</p>"""
    best_objective_not_improving: NotRequired[
        "capo_sagemaker.types.best_objective_not_improving.BestObjectiveNotImproving"
    ]
    """<p>A flag to stop your hyperparameter tuning job if model performance fails to improve as evaluated against an objective function.</p>"""
    convergence_detected: NotRequired[
        "capo_sagemaker.types.convergence_detected.ConvergenceDetected"
    ]
    """<p>A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has detected that your model has converged as evaluated against your objective function.</p>"""

best_objective_not_improving instance-attribute 

best_objective_not_improving: NotRequired[BestObjectiveNotImproving]

A flag to stop your hyperparameter tuning job if model performance fails to improve as evaluated against an objective function.

convergence_detected instance-attribute 

convergence_detected: NotRequired[ConvergenceDetected]

A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has detected that your model has converged as evaluated against your objective function.

target_objective_metric_value instance-attribute 

target_objective_metric_value: NotRequired[TargetObjectiveMetricValue]

The value of the objective metric.