---
library_name: transformers
language:
- fr
base_model: microsoft/trocr-base-handwritten
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: TrOCR Small (Finetuned on French)
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# TrOCR Small (Finetuned on French)

This model is a fine-tuned version of [microsoft/trocr-base-handwritten](https://huggingface.co/microsoft/trocr-base-handwritten) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0871
- Model Preparation Time: 0.0066
- Cer: 0.0134
- Wer: 0.0350
- Ratio: 97.4287

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Model Preparation Time | Cer    | Wer    | Ratio   |
|:-------------:|:------:|:-----:|:---------------:|:----------------------:|:------:|:------:|:-------:|
| 1.359         | 0.0333 | 400   | 1.0638          | 0.0066                 | 0.1715 | 0.3841 | 89.6898 |
| 1.1123        | 0.0667 | 800   | 1.2707          | 0.0066                 | 0.1715 | 0.4437 | 89.7413 |
| 0.872         | 0.1    | 1200  | 0.9230          | 0.0066                 | 0.1305 | 0.3576 | 91.0810 |
| 0.6831        | 0.1333 | 1600  | 0.7046          | 0.0066                 | 0.1195 | 0.2848 | 92.7617 |
| 0.6659        | 0.1667 | 2000  | 0.5952          | 0.0066                 | 0.0841 | 0.2450 | 94.7742 |
| 0.612         | 0.2    | 2400  | 0.5830          | 0.0066                 | 0.1029 | 0.2517 | 93.2609 |
| 0.4865        | 0.2333 | 2800  | 0.5312          | 0.0066                 | 0.0973 | 0.2318 | 94.4422 |
| 0.4922        | 0.2667 | 3200  | 0.5842          | 0.0066                 | 0.0918 | 0.1987 | 95.5454 |
| 0.4152        | 0.3    | 3600  | 0.4215          | 0.0066                 | 0.0664 | 0.1921 | 95.9747 |
| 0.3648        | 0.3333 | 4000  | 0.4264          | 0.0066                 | 0.0608 | 0.1722 | 96.4262 |
| 0.3272        | 0.3667 | 4400  | 0.5209          | 0.0066                 | 0.0653 | 0.1921 | 95.3742 |
| 0.3172        | 0.4    | 4800  | 0.4229          | 0.0066                 | 0.0531 | 0.1788 | 95.8131 |
| 0.2672        | 0.4333 | 5200  | 0.4071          | 0.0066                 | 0.0586 | 0.1921 | 96.0787 |
| 0.2747        | 0.4667 | 5600  | 0.3494          | 0.0066                 | 0.0586 | 0.1656 | 96.2269 |
| 0.2576        | 0.5    | 6000  | 0.3687          | 0.0066                 | 0.0642 | 0.1523 | 96.6562 |
| 0.2138        | 0.5333 | 6400  | 0.3945          | 0.0066                 | 0.0564 | 0.1391 | 96.8775 |
| 0.2197        | 0.5667 | 6800  | 0.3698          | 0.0066                 | 0.0420 | 0.1391 | 97.3293 |
| 0.1908        | 1.0141 | 7200  | 0.3288          | 0.0066                 | 0.0420 | 0.1126 | 97.6500 |
| 0.145         | 1.0474 | 7600  | 0.2655          | 0.0066                 | 0.0332 | 0.0993 | 97.6602 |
| 0.1347        | 1.0808 | 8000  | 0.2659          | 0.0066                 | 0.0365 | 0.1258 | 97.2893 |
| 0.1092        | 1.1141 | 8400  | 0.2496          | 0.0066                 | 0.0343 | 0.1192 | 97.6671 |
| 0.111         | 1.1474 | 8800  | 0.2205          | 0.0066                 | 0.0221 | 0.0861 | 98.4693 |
| 0.1033        | 1.1807 | 9200  | 0.2226          | 0.0066                 | 0.0254 | 0.0927 | 98.1761 |
| 0.0919        | 1.2141 | 9600  | 0.1787          | 0.0066                 | 0.0210 | 0.0728 | 98.6440 |
| 0.074         | 1.2474 | 10000 | 0.1756          | 0.0066                 | 0.0188 | 0.0464 | 99.3030 |
| 0.0833        | 1.2808 | 10400 | 0.1830          | 0.0066                 | 0.0232 | 0.0728 | 98.8762 |
| 0.057         | 1.3141 | 10800 | 0.1675          | 0.0066                 | 0.0133 | 0.0530 | 99.3276 |
| 0.038         | 1.3474 | 11200 | 0.1709          | 0.0066                 | 0.0188 | 0.0596 | 98.9563 |
| 0.0409        | 1.3807 | 11600 | 0.1400          | 0.0066                 | 0.0133 | 0.0530 | 99.2905 |
| 0.0404        | 1.4141 | 12000 | 0.1423          | 0.0066                 | 0.0122 | 0.0464 | 99.2598 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3