---
title: Headlne
emoji: 🔥
colorFrom: indigo
colorTo: pink
sdk: gradio
sdk_version: 5.23.1
app_file: app.py
pinned: false
---

Bias Bin: Bias Detection and Mitigation in Language Models

Bias Bin is an interactive Gradio-based web application for detecting and mitigating gender bias in narrative text. It uses a fine-tuned BERT model and counterfactual data augmentation techniques to highlight and analyze bias in NLP outputs.

🧠 Project Overview

This tool allows users to:
	•	Detect gender bias in input text using a BERT-based classification model.
	•	Explore counterfactual predictions by swapping gendered terms.
	•	Visualize bias scores to understand model behavior.
	•	Demonstrate bias mitigation through gender-swapped text examples.

This project was developed as part of a university coursework in Deep Learning & Generative AI.

📁 Repository Contents
	•	app.py – Main Python file to launch the Gradio web app.
	•	Evaluation&Results.ipynb – Notebook with experiments, model evaluations, and visualizations.
	•	fine_tuned_model.zip – Zip file containing the fine-tuned BERT model (must be extracted).
	•	requirements.txt – List of Python dependencies.

⚙️ Setup Instructions
	1.	Clone the Repository

git clone https://huggingface.co/spaces/aryn25/bias.bin
cd bias.bin

	2.	Install Dependencies

pip install -r requirements.txt

	3.	Extract the Model
Unzip the fine_tuned_model.zip file and place the extracted folder in the project root.
	4.	Run the App

python app.py

	5.	Open in Browser
Visit the Gradio URL printed in the terminal 

📊 Methodology
	•	Model: Fine-tuned BERT classifier trained on gender-labeled narrative datasets.
	•	Bias Detection: Uses counterfactual data augmentation by swapping gendered words (e.g., “he” → “she”).
	•	Metrics: Bias scores are computed based on prediction discrepancies between original and counterfactual samples.

📚 References

This project is built using foundational and peer-reviewed research on:
	•	BERT and Transformer models
	•	Gender bias in NLP
	•	Counterfactual data augmentation
	•	Bias mitigation techniques

Full citation list available in the project report.

📌 Authors

Created by Aryan N. Salge and team as part of the Deep Learning & Generative AI coursework at the National College of Ireland.

📄 License

This project is for educational and research purposes. Please cite appropriately if you use or adapt the work.