pytorch xlm-roberta multilingual arxiv:1606.05250 arxiv:1910.11856 arxiv:1911.02116 transformers MRC SQuAD 1.1 xlm-roberta-large license:apache-2.0

---
tags:
- MRC
- SQuAD 1.1
- xlm-roberta-large
language:
- multilingual
license: apache-2.0
---

# Model description

An XLM-RoBERTa reading comprehension model for [SQuAD 1.1](https://aclanthology.org/D16-1264/).

The model is initialized with  [xlm-roberta-large](https://huggingface.co/xlm-roberta-large/) and fine-tuned on the [SQuAD 1.1 train data](https://huggingface.co/datasets/squad).

## Intended uses & limitations

You can use the raw model for the reading comprehension task. Biases associated with the pre-existing language model, xlm-roberta-large, that we used may be present in our fine-tuned model, squad-v1-xlm-roberta-large. This model is used for zero-shot decoding of [MLQA](https://huggingface.co/datasets/mlqa) and [XQuAD](https://huggingface.co/datasets/xquad) datasets.


## Usage

You can use this model directly with the [PrimeQA](https://github.com/primeqa/primeqa) pipeline for reading comprehension [squad.ipynb](https://github.com/primeqa/primeqa/blob/main/notebooks/mrc/squad.ipynb).

```bibtex
@article{2016arXiv160605250R,
       author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
                 Konstantin and {Liang}, Percy},
        title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
      journal = {arXiv e-prints},
         year = 2016,
          eid = {arXiv:1606.05250},
        pages = {arXiv:1606.05250},
archivePrefix = {arXiv},
       eprint = {1606.05250},
}
```
```bibtex
@article{lewis2019mlqa,
  title={MLQA: Evaluating Cross-lingual Extractive Question Answering},
  author={Lewis, Patrick and Oguz, Barlas and Rinott, Ruty and Riedel, Sebastian and Schwenk, Holger},
  journal={arXiv preprint arXiv:1910.07475},
  year={2019}
}
```

```bibtex
@article{Artetxe:etal:2019,
      author    = {Mikel Artetxe and Sebastian Ruder and Dani Yogatama},
      title     = {On the cross-lingual transferability of monolingual representations},
      journal   = {CoRR},
      volume    = {abs/1910.11856},
      year      = {2019},
      archivePrefix = {arXiv},
      eprint    = {1910.11856}
}
```

```bibtex
@article{DBLP:journals/corr/abs-1911-02116,
  author    = {Alexis Conneau and
               Kartikay Khandelwal and
               Naman Goyal and
               Vishrav Chaudhary and
               Guillaume Wenzek and
               Francisco Guzm{\'{a}}n and
               Edouard Grave and
               Myle Ott and
               Luke Zettlemoyer and
               Veselin Stoyanov},
  title     = {Unsupervised Cross-lingual Representation Learning at Scale},
  journal   = {CoRR},
  volume    = {abs/1911.02116},
  year      = {2019},
  url       = {http://arxiv.org/abs/1911.02116},
  eprinttype = {arXiv},
  eprint    = {1911.02116},
  timestamp = {Mon, 11 Nov 2019 18:38:09 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1911-02116.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
```