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--- |
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language: [bn, hi, hi-en, ka-en, ma-en, mr, ta-en, ur, ur-en, en] |
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license: afl-3.0 |
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--- |
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This model is used detecting **abusive speech** in **Bengali, Devanagari Hindi, Code-mixed Hindi, Code-mixed Kannada, Code-mixed Malayalam, Marathi, Code-mixed Tamil, Urdu, Code-mixed Urdu, and English languages**. The allInOne in the name refers to the Joint training/Cross-lingual training, where the model is trained using all the languages data. It is finetuned on MuRIL model. |
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The model is trained with learning rates of 2e-5. Training code can be found at this [url](https://github.com/hate-alert/IndicAbusive) |
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LABEL_0 :-> Normal |
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LABEL_1 :-> Abusive |
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### For more details about our paper |
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Mithun Das, Somnath Banerjee and Animesh Mukherjee. "[Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages](https://arxiv.org/abs/2204.12543)". Accepted at ACM HT 2022. |
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***Please cite our paper in any published work that uses any of these resources.*** |
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~~~ |
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@article{das2022data, |
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title={Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages}, |
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author={Das, Mithun and Banerjee, Somnath and Mukherjee, Animesh}, |
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journal={arXiv preprint arXiv:2204.12543}, |
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year={2022} |
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} |
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~~~ |
