readme: ---
  tags:
  - MRC
  - SQuAD 1.1
  - roberta-large
  language: en
  license: apache-2.0
  ---
  
  # Model description
  
  An RoBERTa reading comprehension model for [SQuAD 1.1](https://aclanthology.org/D16-1264/).
  
  The model is initialized with  [roberta-large](https://huggingface.co/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, roberta-large, that we used may be present in our fine-tuned model, squad-v1-roberta-large.
  
  
  ## 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{DBLP:journals/corr/abs-1907-11692,
    author    = {Yinhan Liu and
                 Myle Ott and
                 Naman Goyal and
                 Jingfei Du and
                 Mandar Joshi and
                 Danqi Chen and
                 Omer Levy and
                 Mike Lewis and
                 Luke Zettlemoyer and
                 Veselin Stoyanov},
    title     = {RoBERTa: {A} Robustly Optimized {BERT} Pretraining Approach},
    journal   = {CoRR},
    volume    = {abs/1907.11692},
    year      = {2019},
    url       = {http://arxiv.org/abs/1907.11692},
    archivePrefix = {arXiv},
    eprint    = {1907.11692},
    timestamp = {Thu, 01 Aug 2019 08:59:33 +0200},
    biburl    = {https://dblp.org/rec/journals/corr/abs-1907-11692.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
  }
  ```
  