readme: ---
  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
  