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surfiniaburger/unsloth_finetune_ocr_arabic

sourceHugging Faceapache-2.0updated 9mo agoView on Hugging Face

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Model Card

Glimpse: Multi-Modal OCR for RTL Scripts (Arabic & Persian)

Glimpse is a high-precision OCR model specialized for Right-to-Left (RTL) languages. It was developed as part of the ERNIE AI Developer Challenge 2025 to solve the "Script Bias" typically found in general-purpose vision models.

Model Details

—Developed by: surfiniaburger
—License: apache-2.0
—Finetuned from model: unsloth/PaddleOCR-VL
—Architecture: ERNIE-4.5-0.3B Vision-Language Model

📊 Performance Metrics

After 500 steps of fine-tuning, Glimpse achieved the following results on unseen RTL text lines:

—Character Error Rate (CER): 6.97% (Reduced from ~59% baseline)
—Validation Loss: 0.25 (Near-perfect convergence)

📚 Dataset Credit

This model was trained using the Persian & Arabic Text-Line Image OCR Dataset (Medium) curated by Mohammad Reza Hajesmaeili.

—Dataset Source: mohajesmaeili/Persian_Arabic_TextLine_Image_Ocr_Medium
—Content: Diverse text-line images containing complex ligatures and various Arabic/Persian fonts.

🛠 Training Tools

This model was trained 2x faster using Unsloth and Huggingface's TRL library. We utilized QLoRA (4-bit) to ensure efficient memory usage while maintaining high-fidelity weights.