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language:
- ar
license: cc-by-nc-4.0
tags:
- handwritten-text-recognition
- arabic
- khatt
- densenet
- transformer
- transfer-learning
- pytorch
- safetensors
datasets:
- KHATT
- DASTNUS
metrics:
- cer
- wer
pipeline_tag: image-to-text
---
# Arabic Handwritten Text Recognition: DenseNet121-Transformer (Fine-tuned on KHATT)
## Model Description
A lightweight DenseNet121-Transformer architecture for Arabic handwritten line recognition,
pre-trained on the Kurdish DASTNUS dataset and fine-tuned on the KHATT Arabic handwritten dataset.
Uses a triple unified vocabulary covering Kurdish, Arabic, and Urdu scripts (192 tokens). The KHATT dataset is publicly available at https://www.kaggle.com/datasets/iraqyomar/khatt-arabic-hand-written-lines/code (We only used Unique Handwritten Lines)
## Architecture
- **CNN Backbone:** DenseNet-121 (pretrained on ImageNet)
- **Encoder:** 3 Transformer encoder layers
- **Decoder:** 3 Transformer decoder layers
- **Attention Heads:** 8
- **Hidden Size:** 256
- **Parameters:** ~12.8M
- **Vocabulary:** 192 tokens (Triple unified: Kurdish + Arabic + Urdu)
## Transfer Learning Pipeline
1. Pre-trained on Kurdish DASTNUS dataset (with unified vocabulary)
2. Fine-tuned on KHATT Arabic handwritten line dataset
## Performance on KHATT Test Set
| Metric | Value |
|--------|-------|
| CER | 0.1135 |
| WER | 0.4156 |
| CRR | 88.65% |
## Training Data
- **Pre-training:** DASTNUS Kurdish handwritten dataset
- **Fine-tuning:** KHATT Arabic handwritten dataset (5,166 training, 574 validation)
## Usage
```python
from safetensors.torch import load_file
import json
# Load model weights
state_dict = load_file("model.safetensors")
# Load config
with open("config.json", "r") as f:
config = json.load(f)
# Load vocabulary
with open("vocab.json", "r", encoding="utf-8") as f:
vocab = json.load(f)
# Load full unified vocabulary info
with open("unified_vocabulary.json", "r", encoding="utf-8") as f:
unified_vocab = json.load(f)
```
## Citation
[]
## License
This model is released for non-commercial scientific research purposes only.
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