Question Answering
Transformers
PyTorch
TensorBoard
Habana
roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use nbroad/rob-base-superqa2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/rob-base-superqa2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="nbroad/rob-base-superqa2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nbroad/rob-base-superqa2") model = AutoModelForQuestionAnswering.from_pretrained("nbroad/rob-base-superqa2") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 2.0, | |
| "eval_HasAns_exact": 69.19611355371003, | |
| "eval_HasAns_f1": 75.75383941256567, | |
| "eval_HasAns_total": 18423, | |
| "eval_NoAns_exact": 77.6109552879063, | |
| "eval_NoAns_f1": 77.6109552879063, | |
| "eval_NoAns_total": 6061, | |
| "eval_best_exact": 71.27920274464957, | |
| "eval_best_exact_thresh": 0.0, | |
| "eval_best_f1": 76.21356737043324, | |
| "eval_best_f1_thresh": 0.0, | |
| "eval_exact": 71.27920274464957, | |
| "eval_f1": 76.21356737043327, | |
| "eval_samples": 44895, | |
| "eval_total": 24484 | |
| } |