pytorch jax bert text-classification en dataset:hatexplain transformers license:apache-2.0
.gitattributes README.md config.json flax_model.msgpack pytorch_model.bin special_tokens_map.json tokenizer_config.json vocab.txt
---
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}
}
~~~
