- Add Nova training support in Model Trainer
- Removing experiment_config parameter for aws_batch as it is no longer needed with the removal of Estimator
- AWS_Batch: queueing of training jobs with ModelTrainer
- Evaluator handshake with trainer
- Datasets Format validation
- Add validation to bedrock reward models
- Hyperparameter issue fixes, Add validation s3 output path
- Fix the recipe selection for multiple recipe scenario
- Train wait() timeout exception handling
- Update example notebooks to reflect recent code changes
- Update
model_package_group_nameparam tomodel_package_groupin finetuning interfaces - remove
datasetparam for benchmark evaluator
- Fine-tuning SDK: SFT, RLVR, and RLAIF techniques with standardized parameter design
- AIRegistry Integration: Added CRUD operations for datasets and evaluators
- Enhanced Training Experience: Implemented MLFlow metrics tracking and deployment workflows
- Update project dependencies to include submodules: sagemaker-core, sagemaker-train, sagemaker-serve, sagemaker-mlops