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--- |
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license: cc-by-nc-nd-4.0 |
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metrics: |
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- f1 |
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- accuracy |
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base_model: |
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- FacebookAI/xlm-roberta-base |
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language: |
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- en |
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- hi |
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- mr |
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- bn |
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- ta |
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- te |
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- ml |
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- ur |
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pipeline_tag: text-classification |
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tags: |
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- sexism |
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- hate |
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- indic |
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- empowerment |
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- gender |
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--- |
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# Model Card for Model ID |
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Classifies polarised gendered discourse for all indic languages. |
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0=Neutral |
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1=Sexist and misogynistic |
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2=Empowering |
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## Model Details |
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genAMI, paper forthcoming |
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## Author Details |
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Praachi Kumar |
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Research Fellow |
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United Nations University - MERIT |
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### Model Description |
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- **Developed by:** Praachi Kumar |
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- **Model type:** Fine-tuned XLM-RoBERTa base for sequence classification |
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- **Language(s) (NLP):** Multi, focus on Indic |
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- **License:** Non commercial, no derrivatives |
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- **Paper:** Forthcoming |
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## Uses |
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Social science research, intended for academic and nonacademic use |
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## Bias, Risks, and Limitations |
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Social science approaches to annotation, single annotator coded |
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### Recommendations |
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Please contact me at [email protected] for instructions on further use |
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## How to Get Started with the Model |
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Forthcoming |
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## Training Details |
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### Training Data |
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English language Tweets |
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#### Metrics |
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## English Tweets: |
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Macro Average F1 Score: 0.83 |
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Balanced Accuracy: 0.88 |
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## Multilingual Tweets: |
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Macro Average F1 Score: 0.76 |
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Balanced Accuracy: 0.76 |
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### Results |
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Forthcoming |
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## Citation |
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**Model** |
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**BibTeX:** |
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@misc{genami2025, |
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author = {Praachi Kumar}, |
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title = {genAMI}, |
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year = {2025}, |
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month = {March}, |
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day = {13}, |
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howpublished = {\url{https://doi.org/10.57967/hf/5784}} |
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} |
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**APA:** Kumar, P. (2025). genAMI. Hugging Face. https://doi.org/10.57967/hf/5784 |
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**Paper**: Forthcoming |
