Model description
An XLM-RoBERTa reading comprehension model for TyDiQA Primary Tasks.
The model is initialized with xlm-roberta-large and fine-tuned on the TyDiQA train data.
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, tydiqa-primary-task-xlm-roberta-large.
Usage
You can use this model directly with the PrimeQA pipeline for reading comprehension tydiqa.ipynb.
BibTeX entry and citation info
@article{clark-etal-2020-tydi,
title = "{T}y{D}i {QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages",
author = "Clark, Jonathan H. and
Choi, Eunsol and
Collins, Michael and
Garrette, Dan and
Kwiatkowski, Tom and
Nikolaev, Vitaly and
Palomaki, Jennimaria",
journal = "Transactions of the Association for Computational Linguistics",
volume = "8",
year = "2020",
address = "Cambridge, MA",
publisher = "MIT Press",
url = "https://aclanthology.org/2020.tacl-1.30",
doi = "10.1162/tacl_a_00317",
pages = "454--470",
}
@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}
}
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