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README.md
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This is a XLM-Align-Base model trained on CoMMA dataset of 12k samples
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- This is an extension from our previous paper: [Hypers at ComMA@ICON: Modelling Aggressiveness, Gender Bias and Communal Bias Identification](https://arxiv.org/abs/2112.15417).
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## Example Usage
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### Some concerns
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- Note: The model is trained on relatively lower samples (i.e 12k) but with mix of four languages Hindi, Bengali, Meitei, and English. It contains both native on codemixed scripts, So the model might perform poorly on many text samples and might not generalize well.
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This is a XLM-Align-Base model trained on CoMMA dataset of 12k samples
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- This is an extension work from our previous paper: [Hypers at ComMA@ICON: Modelling Aggressiveness, Gender Bias and Communal Bias Identification](https://arxiv.org/abs/2112.15417).
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## Example Usage
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### Some concerns
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- Note: The model is trained on relatively lower samples (i.e 12k) but with mix of four languages Hindi, Bengali, Meitei, and English. It contains both native on codemixed scripts, So the model might perform poorly on many text samples and might not generalize well.
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## Bibtex
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```
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@article{Benhur2021HypersAC,
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title={Hypers at ComMA@ICON: Modelling Aggressiveness, Gender Bias and Communal Bias Identification},
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author={Sean Benhur and Roshan Nayak and Kanchana Sivanraju and Adeep Hande and Subalalitha Chinnaudayar Navaneethakrishnan and Ruba Priyadharshini and Bharathi Raja Chakravarthi6},
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journal={ArXiv},
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year={2021},
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volume={abs/2112.15417}
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}
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```
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