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donut-base-hangul-handwritten-KMOU
This model is a fine-tuned version of naver-clova-ix/donut-base on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.5986 | 1.0 | 157 | 2.9011 |
| 0.6912 | 2.0 | 314 | 0.4334 |
| 0.3317 | 3.0 | 471 | 0.2250 |
| 0.2029 | 4.0 | 628 | 0.1379 |
| 0.1587 | 5.0 | 785 | 0.0901 |
| 0.0963 | 6.0 | 942 | 0.0609 |
| 0.0812 | 7.0 | 1099 | 0.0410 |
| 0.0755 | 8.0 | 1256 | 0.0289 |
| 0.0471 | 9.0 | 1413 | 0.0191 |
| 0.0368 | 10.0 | 1570 | 0.0140 |
| 0.0247 | 11.0 | 1727 | 0.0088 |
| 0.023 | 12.0 | 1884 | 0.0065 |
| 0.0239 | 13.0 | 2041 | 0.0045 |
| 0.0139 | 14.0 | 2198 | 0.0036 |
| 0.0166 | 15.0 | 2355 | 0.0025 |
| 0.0144 | 16.0 | 2512 | 0.0020 |
| 0.0144 | 17.0 | 2669 | 0.0017 |
| 0.012 | 18.0 | 2826 | 0.0012 |
| 0.0085 | 19.0 | 2983 | 0.0008 |
| 0.0063 | 20.0 | 3140 | 0.0010 |
| 0.0054 | 21.0 | 3297 | 0.0007 |
| 0.0074 | 22.0 | 3454 | 0.0008 |
| 0.0056 | 23.0 | 3611 | 0.0006 |
| 0.0048 | 24.0 | 3768 | 0.0004 |
| 0.0055 | 25.0 | 3925 | 0.0003 |
| 0.0053 | 26.0 | 4082 | 0.0003 |
| 0.0054 | 27.0 | 4239 | 0.0003 |
| 0.0067 | 28.0 | 4396 | 0.0004 |
| 0.0042 | 29.0 | 4553 | 0.0002 |
| 0.0028 | 30.0 | 4710 | 0.0003 |
| 0.0036 | 31.0 | 4867 | 0.0002 |
| 0.004 | 32.0 | 5024 | 0.0003 |
| 0.0041 | 33.0 | 5181 | 0.0001 |
| 0.005 | 34.0 | 5338 | 0.0002 |
| 0.0025 | 35.0 | 5495 | 0.0002 |
| 0.004 | 36.0 | 5652 | 0.0001 |
| 0.0038 | 37.0 | 5809 | 0.0001 |
| 0.0033 | 38.0 | 5966 | 0.0001 |
| 0.0026 | 39.0 | 6123 | 0.0001 |
| 0.0052 | 40.0 | 6280 | 0.0001 |
| 0.0051 | 41.0 | 6437 | 0.0001 |
| 0.0019 | 42.0 | 6594 | 0.0001 |
| 0.0036 | 43.0 | 6751 | 0.0001 |
| 0.0053 | 44.0 | 6908 | 0.0001 |
| 0.0018 | 45.0 | 7065 | 0.0001 |
| 0.0033 | 46.0 | 7222 | 0.0001 |
| 0.0061 | 47.0 | 7379 | 0.0001 |
| 0.0023 | 48.0 | 7536 | 0.0000 |
| 0.0023 | 49.0 | 7693 | 0.0000 |
| 0.0048 | 50.0 | 7850 | 0.0000 |
Framework versions
- Transformers 4.28.1
- Pytorch 1.10.0+cu111
- Datasets 2.11.0
- Tokenizers 0.13.3
