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--- |
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tags: |
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- image-to-text |
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language: ar |
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model-index: |
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- name: ArOCR |
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results: |
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- task: |
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name: Optical Charater Recogntion |
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type: image-to-text |
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metrics: |
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- name: Test CER |
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type: cer |
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value: 0.02 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ArOCR |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0407 |
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- Cer: 0.0200 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 1.6164 | 0.59 | 1000 | 1.4109 | 0.5793 | |
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| 0.3434 | 1.18 | 2000 | 0.3876 | 0.2176 | |
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| 0.1679 | 1.77 | 3000 | 0.2262 | 0.1186 | |
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| 0.0816 | 2.37 | 4000 | 0.1274 | 0.0634 | |
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| 0.0421 | 2.96 | 5000 | 0.0817 | 0.0381 | |
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| 0.0067 | 3.55 | 6000 | 0.0520 | 0.0265 | |
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| 0.0044 | 4.14 | 7000 | 0.0469 | 0.0215 | |
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| 0.0027 | 4.73 | 8000 | 0.0407 | 0.0200 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.9.1 |
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- Datasets 2.1.0 |
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- Tokenizers 0.11.6 |
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