readme: ---
  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
  should probably proofread and complete it, then remove this comment. -->
  
  # 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
  