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