readme: ---
  language:
  - en
  tags:
  - text2text-generation
  license: mit
  datasets:
  - wikifactcheck
  widget:
  - text: "Little Miss Sunshine was filmed over 30 days."
  ---
  # BART base negative claim generation model
  
  This is a BART-based model fine-tuned for negative claim generation. This model is used in the data augmentation process described in the paper [CrossAug: A Contrastive Data Augmentation Method for Debiasing Fact Verification Models](https://arxiv.org/abs/2109.15107). The model has been fine-tuned using the parallel and opposing claims from WikiFactCheck-English dataset.
  
  ## Usage
  
  ```python
  import torch
  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
  
  model_name = 'minwhoo/bart-base-negative-claim-generation'
  tokenizer = AutoTokenizer.from_pretrained(model_name)
  
  model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
  model.to('cuda' if torch.cuda.is_available() else 'cpu')
  
  examples = [
      "Little Miss Sunshine was filmed over 30 days.",
      "Magic Johnson did not play for the Lakers.",
      "Claire Danes is wedded to an actor from England."
  ]
  
  batch = tokenizer(examples, max_length=1024, padding=True, truncation=True, return_tensors="pt")
  out = model.generate(batch['input_ids'].to(model.device), num_beams=5)
  negative_examples = tokenizer.batch_decode(out, skip_special_tokens=True)
  print(negative_examples)
  # ['Little Miss Sunshine was filmed less than 3 days.', 'Magic Johnson played for the Lakers.', 'Claire Danes is married to an actor from France.']
  ```
  
  ## Citation
  
  ```
  @inproceedings{lee2021crossaug,
    title={CrossAug: A Contrastive Data Augmentation Method for Debiasing Fact Verification Models},
    author={Minwoo Lee and Seungpil Won and Juae Kim and Hwanhee Lee and Cheoneum Park and Kyomin Jung},
    booktitle={Proceedings of the 30th ACM International Conference on Information & Knowledge Management},
    publisher={Association for Computing Machinery},
    series={CIKM '21},
    year={2021}
  }
  ```