# Azhar_Model_v0.2_Final

## 📜 Project Description
This model is a fine-tuned version of Qwen2.5-7B optimized for Islamic Jurisprudence (Fiqh) using the Shamela Library corpus. 

## 📊 Training Specifications
- **Base Model:** Qwen2.5-7B
- **Training Data:** 20,000 high-quality juristic records from Shamela.
- **Total Processed Tokens:** ~24.5 Million Tokens.
- **Optimization Steps:** 3,000 Steps.
- **Effective Batch Size:** 16 (via Gradient Accumulation).
- **Hardware:** Kaggle Dual T4 GPUs.
- **Total Processed Tokens:** 24,576,000
- **Loss Improvement:** 85.21%
- **Final Perplexity:** 9.68
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### 📈 Performance Gains
| Metric | Initial Value | Final Value | Improvement |
| :--- | :--- | :--- | :--- |
| **Cross-Entropy Loss** | 15.3510 | 2.2705 | **85.21%** |
| **Perplexity (PPL)** | 4,643,546.51 | **9.68** | **99.99%** |

### 🧪 Qualitative Comparison Results:
The model was evaluated across 4 paradigms. The **Azhar Hybrid** approach showed:
- **Accuracy:** Significant reduction in juristic hallucinations compared to the Base model.
- **Linguistic Style:** Successful adoption of classical 'Shamela' phrasing and scholarly terminology.
- **Reliability:** High consistency in providing evidence-based rulings (Fiqh).
    
## 🧪 Qualitative Evaluation (Quad-Comparison Analysis)
To ensure reliability, the model was tested across four different paradigms:
1. **Base Model:** Showed 15% accuracy with significant juristic hallucinations.
2. **RAG Only:** Accurate but lacked scholarly linguistic style.
3. **FT Only (Azhar v0.2):** Demonstrated "Juristic Intuition" and high fluency in classical Arabic.
4. **Hybrid (FT+RAG):** The optimal configuration, achieving the highest scores in both factual accuracy and stylistic authenticity.

## 📂 Verification Files
The full comparison results (Base vs RAG vs FT vs Hybrid) are available in the attached `Azhar_Model_Quad_Comparison_v0.1.csv` file in this repository.

## 📉 Visualized Convergence
The training exhibited a stable downward trend in both Loss and Perplexity curves, indicating successful domain adaptation without catastrophic forgetting.

## ⚖️ Ethical Considerations & Use Case
This model is intended for academic and research purposes to assist scholars in navigating classical texts. It should be used as a supplementary tool alongside traditional scholarly verification.
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**Developed by:** MSc. Shamil Al-Mohammedi This model serves as the primary artifact for the research paper: *"Fine-Tuning Large Language Models on Classical Arabic Juristic Corpora: A Case Study on the Shamela Library."*