---
tags:
- generated_from_trainer
- trocr
language: ar
model-index:
- name: TrOCR-Ar-Small
  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-Ar-Small

This model is a fine-tuned version of [microsoft/trocr-small-stage1](https://huggingface.co/microsoft/trocr-small-stage1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2771
- Cer: 0.8211

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.6363        | 0.14  | 1000  | 2.7594          | 0.9370 |
| 2.7508        | 0.29  | 2000  | 2.6589          | 0.8901 |
| 2.6519        | 0.43  | 3000  | 2.6059          | 0.8647 |
| 2.5936        | 0.57  | 4000  | 2.5360          | 0.7941 |
| 2.5069        | 0.72  | 5000  | 2.4701          | 0.8262 |
| 2.4606        | 0.86  | 6000  | 2.4427          | 0.7552 |
| 2.4046        | 1.0   | 7000  | 2.4262          | 0.7822 |
| 2.3628        | 1.15  | 8000  | 2.3880          | 0.8186 |
| 2.3458        | 1.29  | 9000  | 2.3589          | 0.8262 |
| 2.3062        | 1.43  | 10000 | 2.3704          | 0.8693 |
| 2.2884        | 1.58  | 11000 | 2.3065          | 0.8034 |
| 2.263         | 1.72  | 12000 | 2.3413          | 0.8545 |
| 2.2473        | 1.86  | 13000 | 2.3314          | 0.7996 |
| 2.2318        | 2.01  | 14000 | 2.3034          | 0.8254 |
| 2.2004        | 2.15  | 15000 | 2.3068          | 0.8461 |
| 2.1774        | 2.29  | 16000 | 2.2799          | 0.8207 |
| 2.1684        | 2.44  | 17000 | 2.2746          | 0.8249 |
| 2.1637        | 2.58  | 18000 | 2.2540          | 0.7797 |
| 2.1418        | 2.72  | 19000 | 2.2595          | 0.7937 |
| 2.1309        | 2.87  | 20000 | 2.2771          | 0.8211 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6