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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-base-hangul-handwritten-KMOU |
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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-base-hangul-handwritten-KMOU |
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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: 0.0000 |
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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: 64 |
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- eval_batch_size: 64 |
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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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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 50 |
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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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| 3.5986 | 1.0 | 157 | 2.9011 | |
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| 0.6912 | 2.0 | 314 | 0.4334 | |
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| 0.3317 | 3.0 | 471 | 0.2250 | |
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| 0.2029 | 4.0 | 628 | 0.1379 | |
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| 0.1587 | 5.0 | 785 | 0.0901 | |
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| 0.0963 | 6.0 | 942 | 0.0609 | |
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| 0.0812 | 7.0 | 1099 | 0.0410 | |
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| 0.0755 | 8.0 | 1256 | 0.0289 | |
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| 0.0471 | 9.0 | 1413 | 0.0191 | |
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| 0.0368 | 10.0 | 1570 | 0.0140 | |
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| 0.0247 | 11.0 | 1727 | 0.0088 | |
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| 0.023 | 12.0 | 1884 | 0.0065 | |
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| 0.0239 | 13.0 | 2041 | 0.0045 | |
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| 0.0139 | 14.0 | 2198 | 0.0036 | |
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| 0.0166 | 15.0 | 2355 | 0.0025 | |
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| 0.0144 | 16.0 | 2512 | 0.0020 | |
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| 0.0144 | 17.0 | 2669 | 0.0017 | |
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| 0.012 | 18.0 | 2826 | 0.0012 | |
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| 0.0085 | 19.0 | 2983 | 0.0008 | |
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| 0.0063 | 20.0 | 3140 | 0.0010 | |
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| 0.0054 | 21.0 | 3297 | 0.0007 | |
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| 0.0074 | 22.0 | 3454 | 0.0008 | |
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| 0.0056 | 23.0 | 3611 | 0.0006 | |
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| 0.0048 | 24.0 | 3768 | 0.0004 | |
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| 0.0055 | 25.0 | 3925 | 0.0003 | |
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| 0.0053 | 26.0 | 4082 | 0.0003 | |
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| 0.0054 | 27.0 | 4239 | 0.0003 | |
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| 0.0067 | 28.0 | 4396 | 0.0004 | |
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| 0.0042 | 29.0 | 4553 | 0.0002 | |
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| 0.0028 | 30.0 | 4710 | 0.0003 | |
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| 0.0036 | 31.0 | 4867 | 0.0002 | |
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| 0.004 | 32.0 | 5024 | 0.0003 | |
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| 0.0041 | 33.0 | 5181 | 0.0001 | |
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| 0.005 | 34.0 | 5338 | 0.0002 | |
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| 0.0025 | 35.0 | 5495 | 0.0002 | |
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| 0.004 | 36.0 | 5652 | 0.0001 | |
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| 0.0038 | 37.0 | 5809 | 0.0001 | |
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| 0.0033 | 38.0 | 5966 | 0.0001 | |
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| 0.0026 | 39.0 | 6123 | 0.0001 | |
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| 0.0052 | 40.0 | 6280 | 0.0001 | |
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| 0.0051 | 41.0 | 6437 | 0.0001 | |
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| 0.0019 | 42.0 | 6594 | 0.0001 | |
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| 0.0036 | 43.0 | 6751 | 0.0001 | |
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| 0.0053 | 44.0 | 6908 | 0.0001 | |
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| 0.0018 | 45.0 | 7065 | 0.0001 | |
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| 0.0033 | 46.0 | 7222 | 0.0001 | |
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| 0.0061 | 47.0 | 7379 | 0.0001 | |
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| 0.0023 | 48.0 | 7536 | 0.0000 | |
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| 0.0023 | 49.0 | 7693 | 0.0000 | |
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| 0.0048 | 50.0 | 7850 | 0.0000 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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