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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-base-full_text_wt_val_1008 |
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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-full_text_wt_val_1008 |
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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: 0.1060 |
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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: 10 |
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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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| 1.9227 | 0.2 | 100 | 0.6985 | |
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| 0.6852 | 0.4 | 200 | 0.4421 | |
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| 0.5102 | 0.6 | 300 | 0.3346 | |
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| 0.4178 | 0.79 | 400 | 0.2886 | |
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| 0.4476 | 0.99 | 500 | 0.2455 | |
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| 0.2931 | 1.19 | 600 | 0.2287 | |
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| 0.2647 | 1.39 | 700 | 0.2072 | |
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| 0.2418 | 1.59 | 800 | 0.1905 | |
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| 0.3031 | 1.79 | 900 | 0.1754 | |
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| 0.2306 | 1.98 | 1000 | 0.1667 | |
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| 0.2031 | 2.18 | 1100 | 0.1619 | |
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| 0.1918 | 2.38 | 1200 | 0.1536 | |
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| 0.1802 | 2.58 | 1300 | 0.1504 | |
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| 0.1646 | 2.78 | 1400 | 0.1436 | |
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| 0.1816 | 2.98 | 1500 | 0.1379 | |
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| 0.1344 | 3.17 | 1600 | 0.1395 | |
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| 0.1752 | 3.37 | 1700 | 0.1336 | |
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| 0.1388 | 3.57 | 1800 | 0.1306 | |
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| 0.1402 | 3.77 | 1900 | 0.1262 | |
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| 0.1123 | 3.97 | 2000 | 0.1277 | |
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| 0.144 | 4.17 | 2100 | 0.1248 | |
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| 0.1077 | 4.37 | 2200 | 0.1226 | |
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| 0.1134 | 4.56 | 2300 | 0.1186 | |
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| 0.1192 | 4.76 | 2400 | 0.1179 | |
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| 0.1142 | 4.96 | 2500 | 0.1194 | |
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| 0.1426 | 5.16 | 2600 | 0.1202 | |
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| 0.1022 | 5.36 | 2700 | 0.1165 | |
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| 0.0815 | 5.56 | 2800 | 0.1164 | |
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| 0.1096 | 5.75 | 2900 | 0.1166 | |
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| 0.0866 | 5.95 | 3000 | 0.1121 | |
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| 0.1148 | 6.15 | 3100 | 0.1122 | |
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| 0.0771 | 6.35 | 3200 | 0.1129 | |
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| 0.0996 | 6.55 | 3300 | 0.1096 | |
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| 0.0622 | 6.75 | 3400 | 0.1099 | |
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| 0.0985 | 6.94 | 3500 | 0.1092 | |
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| 0.0684 | 7.14 | 3600 | 0.1097 | |
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| 0.0669 | 7.34 | 3700 | 0.1086 | |
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| 0.0624 | 7.54 | 3800 | 0.1088 | |
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| 0.0763 | 7.74 | 3900 | 0.1069 | |
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| 0.0579 | 7.94 | 4000 | 0.1060 | |
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| 0.0623 | 8.13 | 4100 | 0.1083 | |
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| 0.0599 | 8.33 | 4200 | 0.1058 | |
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| 0.0625 | 8.53 | 4300 | 0.1073 | |
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| 0.0499 | 8.73 | 4400 | 0.1059 | |
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| 0.0628 | 8.93 | 4500 | 0.1059 | |
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| 0.0684 | 9.13 | 4600 | 0.1063 | |
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| 0.0472 | 9.33 | 4700 | 0.1056 | |
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| 0.068 | 9.52 | 4800 | 0.1057 | |
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| 0.06 | 9.72 | 4900 | 0.1062 | |
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| 0.0636 | 9.92 | 5000 | 0.1060 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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