TongJiL

> It may be installing old versions of the library so you have to pick up the corresponding version of the example (cc @philschmid for the exact versions) Thank you...

@philschmid ``` import sagemaker from sagemaker.huggingface import HuggingFace role = sagemaker.get_execution_role() hyperparameters = { 'model_name_or_path':'deepset/roberta-base-squad2', 'output_dir':'/opt/ml/model' 'train_file';'/opt/ml/input/data/train/qa_train_data.csv' } git_config = {'repo': 'https://github.com/huggingface/transformers.git','branch': 'v4.17.0'} huggingface_estimator = HuggingFace( entry_point='run_qa.py', source_dir='./examples/pytorch/question-answering', instance_type='ml.p3.2xlarge', instance_count=1,...

Turns out the "filed" works for Json but not csv.

I could not be more agree with ngingihy. Could you please give some detail steps for training on a custom dataset?

Could you please also provide the trained results for VeRi? It would be a really big help to me and a lot of people.