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--- |
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license: mit |
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base_model: naver-clova-ix/donut-base |
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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_marriage_RT_539-135_301123 |
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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_marriage_RT_539-135_301123 |
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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: 0.1088 |
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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: 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: 25 |
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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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| 1.1504 | 1.0 | 270 | 0.5023 | |
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| 0.1444 | 2.0 | 540 | 0.2738 | |
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| 0.2701 | 3.0 | 810 | 0.1902 | |
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| 0.3624 | 4.0 | 1080 | 0.1666 | |
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| 0.1274 | 5.0 | 1350 | 0.1542 | |
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| 0.0369 | 6.0 | 1620 | 0.1537 | |
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| 0.0615 | 7.0 | 1890 | 0.1402 | |
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| 0.0271 | 8.0 | 2160 | 0.1293 | |
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| 0.0142 | 9.0 | 2430 | 0.1262 | |
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| 0.2481 | 10.0 | 2700 | 0.1255 | |
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| 0.002 | 11.0 | 2970 | 0.1260 | |
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| 0.0098 | 12.0 | 3240 | 0.1244 | |
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| 0.0045 | 13.0 | 3510 | 0.1214 | |
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| 0.0001 | 14.0 | 3780 | 0.1278 | |
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| 0.0011 | 15.0 | 4050 | 0.1227 | |
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| 0.0006 | 16.0 | 4320 | 0.1226 | |
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| 0.0003 | 17.0 | 4590 | 0.1212 | |
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| 0.0022 | 18.0 | 4860 | 0.1170 | |
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| 0.0002 | 19.0 | 5130 | 0.1141 | |
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| 0.0002 | 20.0 | 5400 | 0.1176 | |
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| 0.0004 | 21.0 | 5670 | 0.1142 | |
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| 0.0001 | 22.0 | 5940 | 0.1096 | |
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| 0.0003 | 23.0 | 6210 | 0.1090 | |
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| 0.0002 | 24.0 | 6480 | 0.1092 | |
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| 0.0001 | 25.0 | 6750 | 0.1088 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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