HuggingFace Model hyperparameter search with ray as backend not saving best trial hyperparameters

I have no problem running this locally, but am encountering an issue using the sagemaker HuggingFace etimator. When running a HUggingFace hyperparameter_search, the hyperparameters for a trial are not saving. Thus, at the end of the tuning job when running best_trial.hyperparameters I get an empty dictionary. I double checked the saved files in the model.tar.gz file and the params.json file is empty.

Local dependency versions:
python = 3.10.11
sagemaker = “2.203.0”
transformers = “4.28.0”
torch = “2.1.2+cpu”
ray = “2.6.3”

Instantiation of sgaemaker hugging face estimator:
transformers_version = ‘4.28’,
pytorch_version = ‘2.0’
py_version = ‘py310’

within sagemaker container run:
os.system(“pip install ray==2.6.3”)