| language: en | |
| # SciBERT-SQuAD-QuAC | |
| This is the [SciBERT language representation model](https://huggingface.co/allenai/scibert_scivocab_uncased) fine tuned for Question Answering. SciBERT is a pre-trained language model based on BERT that has been trained on a large corpus of scientific text. When fine tuning for Question Answering we combined [SQuAD2.0](https://www.aclweb.org/anthology/P18-2124/) and [QuAC](https://arxiv.org/abs/1808.07036) datasets. | |
| If using this model, please cite the following paper: | |
| ``` | |
| @inproceedings{otegi-etal-2020-automatic, | |
| title = "Automatic Evaluation vs. User Preference in Neural Textual {Q}uestion{A}nswering over {COVID}-19 Scientific Literature", | |
| author = "Otegi, Arantxa and | |
| Campos, Jon Ander and | |
| Azkune, Gorka and | |
| Soroa, Aitor and | |
| Agirre, Eneko", | |
| booktitle = "Proceedings of the 1st Workshop on {NLP} for {COVID}-19 (Part 2) at {EMNLP} 2020", | |
| month = dec, | |
| year = "2020", | |
| address = "Online", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://www.aclweb.org/anthology/2020.nlpcovid19-2.15", | |
| doi = "10.18653/v1/2020.nlpcovid19-2.15", | |
| } | |
| ``` | |