readme: ---
  language: en
  license: apache-2.0
  datasets:
    - hatexplain
  ---
  The model is used for classifying a text as **Hatespeech**, **Offensive**, or **Normal**. The model is trained using data from Gab and Twitter and *Human Rationales* were included as part of the training data to boost the performance.
  
  The dataset and models are available here: https://github.com/punyajoy/HateXplain
  
  
  **For more details about our paper**
  
  Binny Mathew, Punyajoy Saha, Seid Muhie Yimam, Chris Biemann, Pawan Goyal, and Animesh Mukherjee "[HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection)". Accepted at AAAI 2021.
  
  ***Please cite our paper in any published work that uses any of these resources.***
  
  ~~~
  @article{mathew2020hatexplain,
    title={HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection},
    author={Mathew, Binny and Saha, Punyajoy and Yimam, Seid Muhie and Biemann, Chris and Goyal, Pawan and Mukherjee, Animesh},
    journal={arXiv preprint arXiv:2012.10289},
    year={2020}
  }
  ~~~
  