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--- |
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tags: |
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- generated_from_trainer |
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- trocr |
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language: ar |
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model-index: |
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- name: TrOCR-Ar-Small |
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results: [] |
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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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# TrOCR-Ar-Small |
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This model is a fine-tuned version of [microsoft/trocr-small-stage1](https://huggingface.co/microsoft/trocr-small-stage1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2771 |
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- Cer: 0.8211 |
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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: 1 |
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- eval_batch_size: 1 |
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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: 3.0 |
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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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| 3.6363 | 0.14 | 1000 | 2.7594 | 0.9370 | |
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| 2.7508 | 0.29 | 2000 | 2.6589 | 0.8901 | |
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| 2.6519 | 0.43 | 3000 | 2.6059 | 0.8647 | |
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| 2.5936 | 0.57 | 4000 | 2.5360 | 0.7941 | |
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| 2.5069 | 0.72 | 5000 | 2.4701 | 0.8262 | |
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| 2.4606 | 0.86 | 6000 | 2.4427 | 0.7552 | |
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| 2.4046 | 1.0 | 7000 | 2.4262 | 0.7822 | |
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| 2.3628 | 1.15 | 8000 | 2.3880 | 0.8186 | |
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| 2.3458 | 1.29 | 9000 | 2.3589 | 0.8262 | |
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| 2.3062 | 1.43 | 10000 | 2.3704 | 0.8693 | |
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| 2.2884 | 1.58 | 11000 | 2.3065 | 0.8034 | |
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| 2.263 | 1.72 | 12000 | 2.3413 | 0.8545 | |
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| 2.2473 | 1.86 | 13000 | 2.3314 | 0.7996 | |
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| 2.2318 | 2.01 | 14000 | 2.3034 | 0.8254 | |
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| 2.2004 | 2.15 | 15000 | 2.3068 | 0.8461 | |
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| 2.1774 | 2.29 | 16000 | 2.2799 | 0.8207 | |
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| 2.1684 | 2.44 | 17000 | 2.2746 | 0.8249 | |
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| 2.1637 | 2.58 | 18000 | 2.2540 | 0.7797 | |
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| 2.1418 | 2.72 | 19000 | 2.2595 | 0.7937 | |
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| 2.1309 | 2.87 | 20000 | 2.2771 | 0.8211 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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