Hate-speech-CNERG/

dehatebert-mono-indonesian

This model is used detecting hatespeech in Indonesian language. The mono in the name refers to the monolingual setting, where the model is trained using only Arabic language data. It is finetuned on multilingual bert model. The model is trained with different learning rates and the best validation score achieved is 0.844494 for a learning rate of 2e-5. Training code can be found at this url

Sai Saketh Aluru, Binny Mathew, Punyajoy Saha and Animesh Mukherjee. "Deep Learning Models for Multilingual Hate Speech Detection". Accepted at ECML-PKDD 2020.

@article{aluru2020deep,
  title={Deep Learning Models for Multilingual Hate Speech Detection},
  author={Aluru, Sai Saket and Mathew, Binny and Saha, Punyajoy and Mukherjee, Animesh},
  journal={arXiv preprint arXiv:2004.06465},
  year={2020}
}