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---
library_name: PyLaia
license: mit
tags:
- PyLaia
- PyTorch
- atr
- htr
- ocr
- historical
- handwritten
metrics:
- CER
- WER
language:
- fr
base_model: Teklia/pylaia-norhand-v3
datasets:
- Teklia/PELLET-Casimir-Marius-line
pipeline_tag: image-to-text
---
# PyLaia - PELLET Casimir Marius
This model performs Handwritten Text Recognition in French. Trained following [Teklia's tutorial](https://doc.arkindex.org/tutorial/).
## Model description
The model has been trained using the PyLaia library on the [PELLET Casimir Marius - Line level](https://huggingface.co./datasets/Teklia/PELLET-Casimir-Marius-line) dataset.
Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.
| set | lines |
| :---- | ----: |
| train | 842 |
| val | 125 |
| test | 122 |
## Evaluation results
The model achieves the following results:
| set | CER (%) | WER (%) | text_line |
| :---- | ------: | ------: | --------: |
| train | 24.17 | 58.12 | 842 |
| val | 22.90 | 58.75 | 125 |
| test | 18.78 | 50.00 | 122 |
## How to use?
Please refer to the [PyLaia documentation](https://atr.pages.teklia.com/pylaia/usage/prediction/) to use this model.
## Cite us!
```bibtex
@inproceedings{pylaia2024,
author = {Tarride, Solène and Schneider, Yoann and Generali-Lince, Marie and Boillet, Mélodie and Abadie, Bastien and Kermorvant, Christopher},
title = {{Improving Automatic Text Recognition with Language Models in the PyLaia Open-Source Library}},
booktitle = {Document Analysis and Recognition - ICDAR 2024},
year = {2024},
publisher = {Springer Nature Switzerland},
address = {Cham},
pages = {387--404},
isbn = {978-3-031-70549-6}
}
```
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