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--- |
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library_name: transformers |
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base_model: microsoft/trocr-base-str |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: microsoft/trocr-base-str |
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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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# microsoft/trocr-base-str |
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This model is a fine-tuned version of [microsoft/trocr-base-str](https://huggingface.co/microsoft/trocr-base-str) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0856 |
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- Cer: 0.0098 |
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- Wer: 0.0573 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 20 |
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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 | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 1.6623 | 1.0 | 217 | 0.4722 | 0.0574 | 0.2340 | |
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| 0.4122 | 2.0 | 434 | 0.3248 | 0.0378 | 0.1585 | |
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| 0.1077 | 3.0 | 651 | 0.0898 | 0.0132 | 0.0722 | |
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| 0.047 | 4.0 | 868 | 0.0848 | 0.0114 | 0.0614 | |
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| 0.0304 | 5.0 | 1085 | 0.0836 | 0.0122 | 0.0634 | |
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| 0.0224 | 6.0 | 1302 | 0.0891 | 0.0104 | 0.0566 | |
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| 0.0154 | 7.0 | 1519 | 0.0873 | 0.0107 | 0.0587 | |
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| 0.0137 | 8.0 | 1736 | 0.0852 | 0.0102 | 0.0560 | |
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| 0.0121 | 9.0 | 1953 | 0.0883 | 0.0107 | 0.0634 | |
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| 0.0095 | 10.0 | 2170 | 0.0829 | 0.0092 | 0.0526 | |
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| 0.0068 | 11.0 | 2387 | 0.0851 | 0.0091 | 0.0519 | |
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| 0.0075 | 12.0 | 2604 | 0.0831 | 0.0102 | 0.0600 | |
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| 0.0055 | 13.0 | 2821 | 0.0824 | 0.0098 | 0.0580 | |
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| 0.0048 | 14.0 | 3038 | 0.0821 | 0.0099 | 0.0587 | |
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| 0.0023 | 15.0 | 3255 | 0.0873 | 0.0096 | 0.0553 | |
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| 0.0018 | 16.0 | 3472 | 0.0835 | 0.0102 | 0.0593 | |
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| 0.0016 | 17.0 | 3689 | 0.0888 | 0.0100 | 0.0600 | |
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| 0.0034 | 18.0 | 3906 | 0.0853 | 0.0094 | 0.0553 | |
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| 0.001 | 19.0 | 4123 | 0.0857 | 0.0096 | 0.0566 | |
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| 0.0013 | 20.0 | 4340 | 0.0856 | 0.0098 | 0.0573 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.19.1 |
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