1 Commits (e805f8e26373b24431401f02ce1a4654cb2d2078)

Author	SHA1	Message	Date
Tesfagabir Meharizghi	a7000ee89e	Callback handler for Amazon SageMaker Experiments (#8587) ... ## Description This PR implements a callback handler for SageMaker Experiments which is similar to that of mlflow. * When creating the callback handler, it takes the experiment's run object as an argument. All the callback outputs are then logged to the run object. * The output of each callback action (e.g., `on_llm_start`) is saved to S3 bucket as json file. * Optionally, you can also log additional information such as the LLM hyper-parameters to the same run object. * Once the callback object is no more needed, you will need to call the `flush_tracker()` method. This makes sure that any intermediate files are deleted. * A separate notebook example is provided to show how the callback is used. @3coins @agola11 --------- Co-authored-by: Tesfagabir Meharizghi <mehariz@amazon.com>	1 year ago