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| license: mit | |
| title: TOSRoberta | |
| sdk: streamlit | |
| emoji: 🚀 | |
| colorFrom: red | |
| colorTo: yellow | |
| # TOSRoberta: Terms of Service Analyzer 📜🤖 | |
| TOSRoberta is an advanced Terms of Service (ToS) analyzer powered by a fine-tuned RoBERTa-large model. It classifies clauses in ToS documents based on their fairness level, helping users quickly identify potentially unfair terms. | |
|  | |
| ## 🌟 Features | |
| - 📊 Analyzes ToS documents and classifies clauses into three categories: | |
| - ✅ Clearly Fair | |
| - ⚠️ Potentially Unfair | |
| - ❌ Clearly Unfair | |
| - 📁 Supports both PDF and text file uploads | |
| - 💻 User-friendly web interface built with Streamlit | |
| - 🧠 Powered by a fine-tuned RoBERTa-large model (CodeHima/Tos-Roberta) | |
| ## 🚀 Model Performance | |
| Our Tos-Roberta model demonstrates strong performance on the task of ToS clause classification: | |
| - **Validation Accuracy**: 89.64% | |
| - **Test Accuracy**: 85.84% | |
| Detailed performance metrics per epoch: | |
| | Epoch | Training Loss | Validation Loss | Accuracy | F1 Score | Precision | Recall | | |
| |-------|---------------|-----------------|----------|----------|-----------|----------| | |
| | 1 | 0.443500 | 0.398950 | 0.874699 | 0.858838 | 0.862516 | 0.874699 | | |
| | 2 | 0.416400 | 0.438409 | 0.853012 | 0.847317 | 0.849916 | 0.853012 | | |
| | 3 | 0.227700 | 0.505879 | 0.896386 | 0.893325 | 0.891521 | 0.896386 | | |
| | 4 | 0.052600 | 0.667532 | 0.891566 | 0.893167 | 0.895115 | 0.891566 | | |
| | 5 | 0.124200 | 0.747090 | 0.884337 | 0.887412 | 0.891807 | 0.884337 | | |
| ## 📁 Project Structure | |
| ``` | |
| tos-analyzer/ | |
| │ | |
| ├── app.py | |
| ├── requirements.txt | |
| ├── utils/ | |
| │ ├── __init__.py | |
| │ ├── text_processing.py | |
| │ └── model_utils.py | |
| └── README.md | |
| ``` | |
| ## 🛠️ Installation | |
| 1. Clone the repository: | |
| ``` | |
| git clone https://github.com/HimanshuMohanty-Git24/TOSRoberta.git | |
| cd TOSRoberta | |
| ``` | |
| 2. Install the required dependencies: | |
| ``` | |
| pip install -r requirements.txt | |
| ``` | |
| 3. Run the Streamlit app: | |
| ``` | |
| streamlit run app.py | |
| ``` | |
| ## 📊 Training Visualization | |
| We used Weights & Biases for monitoring the training process. Here's a glimpse of our training metrics: | |
|  | |
| ## 🤝 Contributing | |
| Contributions are welcome! Please feel free to submit a Pull Request. | |
| ## 📄 License | |
| This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. | |
| ## 🙏 Acknowledgements | |
| - [Hugging Face](https://huggingface.co/) for the Transformers library | |
| - [Streamlit](https://streamlit.io/) for the easy-to-use web app framework | |
| - [Weights & Biases](https://wandb.ai/) for experiment tracking | |
| ## 📬 Contact | |
| Himanshu Mohanty - [CodingHima](https://x.com/CodingHima) - codehimanshu24@gmail.com | |
| Project Link: [https://github.com/HimanshuMohanty-Git24/TOSRoberta](https://github.com/HimanshuMohanty-Git24/TOSRoberta) | |
| --- | |
| ⭐️ If you find this project useful, please consider giving it a star! |