Update README.md

README.md

@@ -33,15 +33,15 @@ size_categories:
 
 ## 📋 Dataset Summary
 
-The QARI Markdown Mixed Dataset is a specialized synthetic dataset designed for training Arabic OCR models with a focus on complex document layouts and HTML structure understanding. 
+The QARI v0.3 Markdown Mixed Dataset is a specialized synthetic dataset designed for training Arabic OCR models with a focus on complex document layouts and HTML structure understanding. 
 This dataset is part of the QARI-OCR project, which achieves state-of-the-art performance in Arabic text recognition.
 
-This dataset contains **50,000 synthetically generated Arabic document images** with corresponding ground truth text in HTML/Markdown format, featuring:
+This dataset contains **37,000 synthetically generated Arabic document images** (29.6k train, 3.7k validation, 3.7k test) with corresponding ground truth text in HTML/Markdown format, featuring:
 - 🔤 **Full diacritical marks (tashkeel)** support
 - 📝 **Mixed font sizes** within documents (headers, body text, annotations)
 - 🎨 **12 distinct Arabic fonts** ranging from common Naskh to ornate calligraphic styles
 - 📄 **Realistic document layouts** with structural HTML tags
-- 🖼️ **Three degradation levels**: Clean, Moderate, and Heavy
+- 🖼️ **Multiple text sources** including Basma2423 and YoussefAnwar Arabic news
 
 ## 🎯 Intended Use
 
@@ -55,16 +55,57 @@ This dataset is specifically designed for:
 
 | Metric | Value |
 |--------|-------|
-| **Total Images** | 50,000 |
-| **Text Sources** | Modern news articles + Classical Islamic corpus |
+| **Total Images** | 37,000 |
+| **Train Set** | 29,600 (80%) |
+| **Validation Set** | 3,700 (10%) |
+| **Test Set** | 3,700 (10%) |
+| **Text Sources** | oddadmix/Basma2423-Text-with-Diacritics-Correction + YoussefAnwar/Arabic-news |
 | **Font Variety** | 12 Arabic fonts |
 | **Font Size Range** | 14px - 100px |
-| **Degradation Types** | 3 (Clean, Moderate, Heavy) |
 | **Diacritics Support** | ✅ Full tashkeel |
 | **HTML Structure** | ✅ Preserved |
 | **Layout Complexity** | ✅ High (mixed sizes, headers) |
 
+## 🔧 Data Generation Pipeline
 
+<div align="center">
+
+| Stage | Process | Details |
+|-------|---------|---------|
+| **1. Text Collection** | Source gathering | Basma2423 (with diacritics) + YoussefAnwar Arabic news |
+| **2. HTML Templating** | Layout generation | Mixed font sizes, structural elements |
+| **3. Rendering** | WeasyPrint → PDF → Image | High-quality document rendering |
+| **4. Degradation** | Synthetic noise | Clean / Moderate / Heavy variants |
+
+</div>
 
+## 📈 Model Performance
+
+When used to train QARI v0.3, this dataset enables:
+
+| Metric | Score |
+|--------|-------|
+| **Character Error Rate (CER)** | 0.300 |
+| **Word Error Rate (WER)** | 0.485 |
+| **BLEU Score** | 0.545 |
+| **Training Time** | 11 hours |
+| **CO₂ Emissions** | 1.88 kg eq. |
+
+### Key Advantages:
+- 📐 **Superior layout understanding** compared to plain text models
+- 🏷️ **HTML tag preservation** for structured document conversion
+- ⚡ **Resource efficient** - 5x less training time than larger datasets
+- 🎯 **Specialized performance** for document structure tasks
+
+## Citation
+
+```markdown
+@article{wasfy2025qari,
+  title={QARI-OCR: High-Fidelity Arabic Text Recognition through Multimodal Large Language Model Adaptation},
+  author={Wasfy, Ahmed and Nacar, Omer and Elkhateb, Abdelakreem and Reda, Mahmoud and Elshehy, Omar and Ammar, Adel and Boulila, Wadii},
+  journal={arXiv preprint arXiv:2506.02295},
+  year={2025}
+}
+```