| # Transformer QG on SQuAD | |
| The inputs of the model refers to | |
| ``` | |
| we integrate C and A into a new C' in the following form. | |
| C' = [c1, c2, ..., [HL], a1, ..., a|A|, [HL], ..., c|C|] | |
| ``` | |
| > Proposed by [Ying-Hong Chan & Yao-Chung Fan. (2019). A Re-current BERT-based Model for Question Generation.](https://www.aclweb.org/anthology/D19-5821/) | |
| More detail: [p208p2002/Transformer-QG-on-SQuAD](https://github.com/p208p2002/Transformer-QG-on-SQuAD) | |
| ## Features | |
| - Fully pipline from fine-tune to evaluation | |
| - Support most of state of the art models | |
| - Fast deploy as a API server | |
| ## Data setting | |
| We report two dataset setting as Follow | |
| ### SQuAD | |
| - train: 87599 | |
| - validation: 10570 | |
| > [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://arxiv.org/abs/1606.05250) | |
| ### SQuAD NQG | |
| - train: 75722 | |
| - dev: 10570 | |
| - test: 11877 | |
| > [Learning to Ask: Neural Question Generation for Reading Comprehension](https://arxiv.org/abs/1705.00106) | |
| ## Available models | |
| - BART | |
| - GPT2 | |
| - T5 | |
| ## Expriments | |
| We report score with `NQG Scorer` which is using in SQuAD NQG. | |
| If not special explanation, the size of the model defaults to "base". | |
| ### SQuAD | |
| Model |Bleu 1|Bleu 2|Bleu 3|Bleu 4|METEOR|ROUGE-L| | |
| ---------------------------------|------|------|------|------|------|-------| | |
| BART-HLSQG |54.67 |39.26 |30.34 |24.15 |25.43 |52.64 | | |
| GPT2-HLSQG |49.31 |33.95 |25.41| 19.69 |22.29 |48.82 | | |
| T5-HLSQG |54.29 |39.22 |30.43 |24.26 |25.56 |53.11 | | |
| ### SQuAD NQG | |
| Model |Bleu 1|Bleu 2|Bleu 3|Bleu 4|METEOR|ROUGE-L| | |
| ---------------------------------|------|------|------|------|------|-------| | |
| BERT-HLSQG (Chan et al.) |49.73 |34.60 |26.13 |20.33 |23.88 |48.23 | | |
| BART-HLSQG |54.12 |38.19 |28.84 |22.35 |24.55 |51.03 | | |
| GPT2-HLSQG |49.82 |33.69 |24.71 |18.63 |21.90 |47.60 | | |
| T5-HLSQG |53.13 |37.60 |28.62 |22.38 |24.48 |51.20 | |