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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