How to configure Debugger built-in rules
Note
After careful consideration, we have made the decision to close new customer access to Amazon Sagemaker Debugger, effective 7/30/26. Existing customers can continue to use the service as normal. Amazon continues to invest in security and availability improvements for Debugger, but we do not plan to introduce new features. For more information, see Debugger availability change.
In the following topics, you'll learn how to use the SageMaker Debugger built-in
rules. Amazon SageMaker Debugger's built-in rules analyze tensors emitted during the training of a model. SageMaker AI
Debugger offers the Rule API operation that monitors training job progress and
errors for the success of training your model. For example, the rules can detect whether
gradients are getting too large or too small, whether a model is overfitting or
overtraining, and whether a training job does not decrease loss function and improve. To see
a full list of available built-in rules, see List of Debugger built-in rules.
Topics
For an advanced configuration of the Debugger built-in rules using the CreateTrainingJob API,
see Configure Debugger using SageMaker API.