Update README.md
Browse filesπ Production-Ready
This model works out of the box with:
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FastAPI backends
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Hugging Face pipeline
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Gradio / Streamlit frontends
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Real-time inference on CPU/GPU
Let me know if you'd like help with a live demo or deployment script.
π€ Let's Connect
Crafted with care by <span style="color:#48b2f7; font-weight:600;">Raghavendra</span> π οΈ
If this model helps your project, please β it, give feedback, or open issues!
Fork it to adapt it for your domain β or reach out if you want help creating one.
README.md
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A fine-tuned [RoBERTa-base](https://huggingface.co/roberta-base) model for **binary sentiment classification** (positive/negative).
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Trained on a custom dataset across multiple sources including tweets, social comments, and headlines to handle **real-world tone detection**.
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## π§ Model Details
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| Framework | π€ Transformers |
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| Model Size | ~125M parameters |
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## π Evaluation (on 20% held-out test set)
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| Metric | Score |
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| Precision | 92% |
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| Recall | 89% |
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## π§ How to Use
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```bash
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pip install transformers torch
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```
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## π¬ Feedback & Collaboration
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Built by <span style="color:lightskyblue; font-weight:600;">Raghavendra</span>
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If you find this useful, leave a β on the repo or reach out for collaborations.
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You can also clone/fork and adapt it to your own domain-specific datasets!
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A fine-tuned [RoBERTa-base](https://huggingface.co/roberta-base) model for **binary sentiment classification** (positive/negative).
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Trained on a custom dataset across multiple sources including tweets, social comments, and headlines to handle **real-world tone detection**.
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Use this model to build sentiment-aware applications, feedback classifiers, social media monitoring tools, or LLM content filters.
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## π§ Model Details
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| Framework | π€ Transformers |
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| Model Size | ~125M parameters |
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## π Evaluation (on 20% held-out test set)
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| Metric | Score |
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| Precision | 92% |
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| Recall | 89% |
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## βοΈ Quick Start
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### π‘ Install Required Libraries
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```bash
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pip install transformers torch
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