tags:
- MRC
- TyDiQA
- xlm-roberta-large
language:
- multilingual
Model description
Reading comprehension, XLM-RoBERTa model for TyDiQA Primary Tasks.
Passage selection task (SelectP): Given a list of the passages in the article, return either (a) the index of the passage that answers the question or (b) NULL if no such passage exists.
Minimal answer span task (MinSpan): Given the full text of an article, return one of (a) the start and end byte indices of the minimal span that completely answers the question; (b) YES or NO if the question requires a yes/no answer and we can draw a conclusion from the passage; (c) NULL if it is not possible to produce a minimal answer for this question.
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.
Usage
You can use this model directly with the PrimeQA pipeline for reading comprehension tydiqa.ipynb.
BibTeX entry and citation info
@article{tydiqa,
title = {TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages},
author = {Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki}
year = {2020},
journal = {Transactions of the Association for Computational Linguistics}
}