| # XLNet Fine-tuned on SQuAD 2.0 Dataset | |
| [XLNet](https://arxiv.org/abs/1906.08237) jointly developed by Google and CMU and fine-tuned on [SQuAD 2.0](https://rajpurkar.github.io/SQuAD-explorer/) for question answering down-stream task. | |
| ## Training Results (Metrics) | |
| ``` | |
| { | |
| "HasAns_exact": 74.7132253711201 | |
| "HasAns_f1": 82.11971607032643 | |
| "HasAns_total": 5928 | |
| "NoAns_exact": 73.38940285954584 | |
| "NoAns_f1": 73.38940285954584 | |
| "NoAns_total": 5945 | |
| "best_exact": 75.67590331003116 | |
| "best_exact_thresh": -19.554906845092773 | |
| "best_f1": 79.16215426779269 | |
| "best_f1_thresh": -19.554906845092773 | |
| "epoch": 4.0 | |
| "exact": 74.05036637749515 | |
| "f1": 77.74830934598614 | |
| "total": 11873 | |
| } | |
| ``` | |
| ## Results Comparison | |
| | Metric | Paper | Model | | |
| | ------ | --------- | --------- | | |
| | **EM** | **78.46** | **75.68** (-2.78) | | |
| | **F1** | **81.33** | **79.16** (-2.17)| | |
| Better fine-tuned models coming soon. | |
| ## How to Use | |
| ``` | |
| from transformers import XLNetForQuestionAnswering, XLNetTokenizerFast | |
| model = XLNetForQuestionAnswering.from_pretrained('jkgrad/xlnet-base-squadv2) | |
| tokenizer = XLNetTokenizerFast.from_pretrained('jkgrad/xlnet-base-squadv2') | |
| ``` |