Amazon SageMaker Automatic Model Tuning Now Supports Warm Start for Hyperparameter Tuning Jobs
Amazon SageMaker Automatic Model Tuning now supports warm start of hyperparameter tuning jobs. With warm start, a new hyperparameter tuning job can be created using prior knowledge learned from one or more parent tuning jobs. This enables Automatic Model Tuning to complete in less time, which reduces your tuning costs.
Amazon SageMaker Automatic Model Tuning now supports warm start of hyperparameter tuning jobs. With warm start, a new hyperparameter tuning job can be created using prior knowledge learned from one or more parent tuning jobs. This enables Automatic Model Tuning to complete in less time, which reduces your tuning costs.
There are many cases where you might want to leverage the knowledge gained from prior hyperparameter tuning jobs for new jobs. For example, you might start with a small set of hyperparameters to create a baseline model and then add additional parameters in subsequent tuning jobs. Similarly, you may have new data that warrant retraining and retuning your model.
Warm start for hyperparameter tuning jobs is available in all AWS regions where Amazon SageMaker is available today. For more information, please visit the product pages.