| Main Script: QuestionAnswering.py | |
| The script uses HuggingFace library for managing the datasets, importing/exporting models and training the models. | |
| There are various variables at the start of the script. | |
| - train: Training a new model | |
| - PEFT: Whether to use PEFT during training | |
| - tf32/fp16: Mixed precision training choice | |
| - trained_model: Name of trained model (to be pushed to HF Hub) | |
| - train_checkpoint: Checkpoint of training (None by default) | |
| - squad_shift: Whether to include extra data (squadshift) | |
| - base_tokenizer: Tokenizer of base model | |
| - base_model: Pre-trained model | |
| - test: Testing a model | |
| - tokenizer_list/model_list/question_list: Which tokenizer, model and questions to be tested. | |
| CUDA is enabled if applicable. | |
| Require user to login into HuggingFace Hub (via command line token or through script) if training. Alternative is to not push to hub, a local repository will be created. | |
| Huggingface repositories created (models created) | |
| - botcon/XLNET_squad_finetuned_large | |
| - botcon/XLNET_squadshift_finetuned_large | |
| - botcon/LUKE_squad_finetuned_large | |
| - botcon/LUKE_squadshift_finetuned_large | |
| - botcon/LUKE_squad_what | |