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PaddleOCR-VL Egyptian ID OCR (Curriculum Learning)
Fine-tuned PaddleOCR-VL for Egyptian national ID OCR using curriculum learning.
Training
Stage: 1/3 Total Epochs: 2 Best Accuracy: 41.2%
Curriculum Structure
- Pre-train on synthetic Arabic names until saturation
- Curriculum: real→synthetic→real transition
- Polish on real data with lower LR
Datasets
- Synthetic:
abzoo/arabic-names-synthetic-ocr(2,363 train / 262 val) - Real:
abzoo/egyptian-id-ocr(2,436 train / 211 test)
Results
Accuracy
| Metric | Score |
|---|---|
| Strict | 80/211 (37.9%) |
| Normalized | 87/211 (41.2%) |
Edit Distance Breakdown
| Distance | Count | % |
|---|---|---|
| ✓ Exact (0) | 87 | 41.2% |
| ~ Close (1) | 41 | 19.4% |
| ~ Close (2) | 11 | 5.2% |
| ~ Close (3) | 4 | 1.9% |
| ✗ Wrong (4+) | 68 | 32.2% |
Training History
| Epoch | Stage | Strict | Normalized |
|---|---|---|---|
| 1 | 1 | 31.3% | 35.1% |
| 2 | 1 | 37.9% | 41.2% |
Usage
from unsloth import FastVisionModel
model, tokenizer = FastVisionModel.from_pretrained(
"abzoo/paddleocr-vl-curriculum-015",
load_in_4bit=True,
)
Base Model
unsloth/PaddleOCR-VL- LoRA r=64, alpha=64
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