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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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model-index: |
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- name: donut_pdf_ocr |
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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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# donut_pdf_ocr |
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This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0821 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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: 30 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.6648 | 1.0 | 47 | 0.2550 | |
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| 0.3772 | 2.0 | 94 | 0.0895 | |
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| 0.1732 | 3.0 | 141 | 0.0862 | |
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| 0.1244 | 4.0 | 188 | 0.0718 | |
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| 0.0867 | 5.0 | 235 | 0.0473 | |
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| 0.1035 | 6.0 | 282 | 0.0640 | |
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| 0.1703 | 7.0 | 329 | 0.0877 | |
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| 0.0324 | 8.0 | 376 | 0.0722 | |
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| 0.033 | 9.0 | 423 | 0.0701 | |
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| 0.0404 | 10.0 | 470 | 0.0627 | |
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| 0.0198 | 11.0 | 517 | 0.0770 | |
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| 0.007 | 12.0 | 564 | 0.0730 | |
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| 0.0207 | 13.0 | 611 | 0.0885 | |
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| 0.0528 | 14.0 | 658 | 0.0898 | |
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| 0.0189 | 15.0 | 705 | 0.0588 | |
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| 0.0977 | 16.0 | 752 | 0.0563 | |
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| 0.0542 | 17.0 | 799 | 0.0647 | |
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| 0.0114 | 18.0 | 846 | 0.0674 | |
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| 0.0056 | 19.0 | 893 | 0.0726 | |
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| 0.005 | 20.0 | 940 | 0.0797 | |
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| 0.0005 | 21.0 | 987 | 0.0704 | |
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| 0.0023 | 22.0 | 1034 | 0.0864 | |
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| 0.0105 | 23.0 | 1081 | 0.0830 | |
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| 0.0014 | 24.0 | 1128 | 0.0806 | |
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| 0.0006 | 25.0 | 1175 | 0.0826 | |
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| 0.0012 | 26.0 | 1222 | 0.0790 | |
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| 0.0006 | 27.0 | 1269 | 0.0751 | |
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| 0.0022 | 28.0 | 1316 | 0.0786 | |
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| 0.0075 | 29.0 | 1363 | 0.0816 | |
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| 0.0024 | 30.0 | 1410 | 0.0821 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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