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README.md

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-license: other
-license_name: restricted-use
-license_link: LICENSE
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+# Qwen3-4B (Custom Fine-Tune) Sile
+
+[![HellaSwag acc_norm](https://img.shields.io/badge/HellaSwag_acc_norm-71.1%25-brightgreen)](#benchmark-results)  
+[![ARC-Challenge acc_norm](https://img.shields.io/badge/ARC--Challenge_acc_norm-65.9%25-brightgreen)](#benchmark-results)  
+![Params](https://img.shields.io/badge/Params-4B-blue)  
+![Hardware](https://img.shields.io/badge/Hardware-RTX%203060%2012GB-orange)
+
+---
+
+## Model Summary
+- **Author:** rfcoder0  
+- **Model Type:** Qwen3-4B base, custom fine-tuned  Sile
+- **Hardware Used:** Single RTX 3060 (12 GB) + RTX 3070 (8gb) 
+- **Training:** Proprietary fine-tune on a curated dataset  
+- **Evaluation:** [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness), 5-shot  
+
+This fine-tuned Qwen3-4B demonstrates performance comparable to, and in some cases exceeding, 7B–8B parameter models on standard reasoning and commonsense benchmarks.  
+
+---
+
+## Benchmark Results (5-shot)
+
+| Task          | acc    | acc_norm |
+|---------------|--------|----------|
+| HellaSwag     | 0.540  | 0.711    |
+| ARC-Challenge | 0.615  | 0.659    |
+| MMLU          | *TBD*  | *TBD*    |
+
+*Values are mean ± stderr. Results produced locally with lm-eval-harness, batch_size=1.*  
+
+---
+
+## Comparison (acc_norm)
+
+| Model             | Params | HellaSwag | ARC-Challenge |
+|-------------------|--------|-----------|---------------|
+| **This work**     | 4B     | **0.711** | **0.659**     |
+| Qwen3-8B (base)   | 8B     | ~0.732    | ~0.58         |
+| LLaMA-2-7B        | 7B     | ~0.70–0.72| ~0.55–0.57    |
+| Mistral-7B        | 7B     | ~0.74–0.75| ~0.60–0.62    |
+
+---
+
+## Notes
+- These results were obtained on a **single consumer GPU (RTX 3060) and  RTX 3070 (8gb)**.  
+- The fine-tune procedure and dataset remain proprietary.  
+- Scores indicate that with high-quality data and efficient training, a **4B parameter model can rival or outperform 7B–8B baselines** on reasoning and commonsense benchmarks.  
+
+---
+
+## Usage
+Weights are **not provided**. This repository serves as a **benchmark disclosure**.  
+If you wish to reproduce similar results, see [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) for methodology.  
+
+---
+
+## License
+License: benchmark-only  
+This repo shares evaluation results only.  
+Model weights are not provided.  
+No redistribution or commercial use permitted without permission.
+
+## Support
+If you find this work valuable and want to support further experiments:  
+
+- **Bitcoin:** bc1q76vw4krfx24gvz73pwmhav620xe6fxkxdh0s48 
+- **Other:** Feel free to contact me for additional options.  
+
+---
+
+## Citation
+If you reference these results, please cite this repository:  
+
+```bibtex
+@misc{rfcoder02025qwen4b,
+  title  = {Qwen3-4B (Sile)},
+  author = {Rob Hak},
+  year   = {2025},
+  url    = {https://huggingface.co/rfcoder0/qwen3-4b-custom-Sile}
+}