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donut-base-keyadded
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: 0.2338
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: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.2872 | 1.0 | 141 | 1.2093 |
| 0.791 | 2.0 | 282 | 0.6119 |
| 0.3808 | 3.0 | 423 | 0.4572 |
| 0.6405 | 4.0 | 564 | 0.3678 |
| 0.5345 | 5.0 | 705 | 0.3261 |
| 0.0957 | 6.0 | 846 | 0.2967 |
| 0.2616 | 7.0 | 987 | 0.2722 |
| 0.0842 | 8.0 | 1128 | 0.2622 |
| 0.0524 | 9.0 | 1269 | 0.2507 |
| 0.0905 | 10.0 | 1410 | 0.2458 |
| 0.1562 | 11.0 | 1551 | 0.2369 |
| 0.0478 | 12.0 | 1692 | 0.2338 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
