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🌐 Production-Ready

This model works out of the box with:

βœ… FastAPI backends

βœ… Hugging Face pipeline

βœ… Gradio / Streamlit frontends

βœ… Real-time inference on CPU/GPU

Let me know if you'd like help with a live demo or deployment script.
🀝 Let's Connect

Crafted with care by <span style="color:#48b2f7; font-weight:600;">Raghavendra</span> πŸ› οΈ
If this model helps your project, please ⭐ it, give feedback, or open issues!
Fork it to adapt it for your domain β€” or reach out if you want help creating one.

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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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- > βœ… Use this model to build sentiment-aware applications, feedback classifiers, social media monitoring tools, or LLM content filters.
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-
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- ---
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  ## 🧠 Model Details
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  | Framework | πŸ€— Transformers |
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  | Model Size | ~125M parameters |
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- ---
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-
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  ## πŸ“Š 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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- ---
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-
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- ## πŸ”§ How to Use
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- ### πŸ“¦ Install dependencies
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  ```bash
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- pip install transformers torch
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- ```
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-
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- ## πŸ“¬ Feedback & Collaboration
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-
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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 ⭐ 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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+ βœ… Use this model to build sentiment-aware applications, feedback classifiers, social media monitoring tools, or LLM content filters.
 
 
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  ## 🧠 Model Details
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  | Framework | πŸ€— Transformers |
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  | Model Size | ~125M parameters |
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  ## πŸ“Š 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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+ ## βš™οΈ Quick Start
 
 
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+ ### πŸ’‘ Install Required Libraries
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  ```bash
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+ pip install transformers torch