Update README.md

README.md

@@ -23,29 +23,33 @@ This model is a fine-tuned version of [unsloth/Qwen2-VL-2B-Instruct](unsloth/Qwe
 - **Languages**: Arabic
 - **Tasks**: OCR (Optical Character Recognition)
 
-## Evaluation Results
-
-The fine-tuned model outperforms the base model significantly in terms of Character Error Rate (CER), Word Error Rate (WER), and BLEU score.
-
-### Fine-Tuned Model Performance
-- **Word Error Rate (WER)**: `0.0675`
-- **Character Error Rate (CER)**: `0.0193`
-- **BLEU Score**:
-  - BLEU: `0.8596`
-  - Precision @1: `93.95%`
-  - Precision @2: `88.55%`
-  - Precision @3: `83.82%`
-  - Precision @4: `79.52%`
-
-### Base Model Performance
-- **Word Error Rate (WER)**: `1.3435`
-- **Character Error Rate (CER)**: `1.1915`
-- **BLEU Score**:
-  - BLEU: `0.2007`
-  - Precision @1: `26.85%`
-  - Precision @2: `21.65%`
-  - Precision @3: `18.13%`
-  - Precision @4: `15.39%`
+## Performance Evaluation
+
+The model has been evaluated on standard OCR metrics, including Word Error Rate (WER), Character Error Rate (CER), and BLEU score.
+
+### Metrics
+
+| Model | WER ↓ | CER ↓ | BLEU ↑ |
+|-------|-------|-------|--------|
+| Fine-Tuned Model | 0.068 | 0.019 | 0.860 |
+| Base Model | 1.344 | 1.191 | 0.201 |
+| EasyOCR | 0.908 | 0.617 | 0.152 |
+| Tesseract OCR | 0.428 | 0.226 | 0.410 |
+
+### Key Results
+
+- **WER:** 0.068 (93.2% word accuracy)
+- **CER:** 0.019 (98.1% character accuracy)
+- **BLEU:** 0.860
+
+### Performance Comparison
+
+The Fine-Tuned Model outperforms other solutions with:
+- 95% reduction in WER compared to Base Model
+- 98% reduction in CER compared to Base Model
+- 328% improvement in BLEU score compared to Base Model
+- 84% lower WER than Tesseract OCR
+- 92% lower WER than EasyOCR
 
 ## Performance Comparison Charts