---
tags:
- image-to-text
language: ar
model-index:
- name: ArOCR
  results:
  - task:
      name: Optical Charater Recogntion 
      type: image-to-text
    metrics:
    - name: Test CER
      type: cer
      value: 0.02
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ArOCR

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0407
- Cer: 0.0200

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.6164        | 0.59  | 1000 | 1.4109          | 0.5793 |
| 0.3434        | 1.18  | 2000 | 0.3876          | 0.2176 |
| 0.1679        | 1.77  | 3000 | 0.2262          | 0.1186 |
| 0.0816        | 2.37  | 4000 | 0.1274          | 0.0634 |
| 0.0421        | 2.96  | 5000 | 0.0817          | 0.0381 |
| 0.0067        | 3.55  | 6000 | 0.0520          | 0.0265 |
| 0.0044        | 4.14  | 7000 | 0.0469          | 0.0215 |
| 0.0027        | 4.73  | 8000 | 0.0407          | 0.0200 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.9.1
- Datasets 2.1.0
- Tokenizers 0.11.6