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https://github.com/4darsh-dev/dark_pattern_detector_app

Dark Pattern Detection using fine Tuned BERT Model, powered by CogniGuard project with streamlit web app
https://github.com/4darsh-dev/dark_pattern_detector_app

ai bert bert-fine-tuning classification-model deep-learning nlp

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Dark Pattern Detection using fine Tuned BERT Model, powered by CogniGuard project with streamlit web app

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# Dark Pattern Detection using Fine Tuned BERT Model
A web app built using streamlit powered by CogniGuard project

Live url : https://huggingface.co/spaces/4darsh-Dev/dark_pattern_detector_app

## Cogni-BERT Model Scores

### Sweeps Training Hyperparametrs


BERT Fine-Tuned Sweep training

### Best Model Report


Cogni-BERT Best Model report

## Running Web App Locally

To run web app locally, follow these steps:

1.**Clone the Repo**:
```bash
git clone https://github.com/4darsh-Dev/dark_pattern_detector_app.git
```

1. **Install Requirements**:

```bash
pip install requirements.txt
```

2. **Run the Streamlit App**:

```bash
streamlit run app.py
```

4. **Access Your App**: After running the command, Streamlit will start a local web server and provide a URL where you can access your app. Typically, it will be something like `http://localhost:8501`. Open this URL in your web browser.

5. **Stop the Streamlit Server**: To stop the Streamlit server, go back to the terminal or command prompt where it's running and press `Ctrl + C` to terminate the server.

### Authors

- [@4darsh-Dev(Adarsh Maurya)](https://github.com/4darsh-Dev)