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DonutInvoiceCzechV013
TomasFAV/DonutInvoiceCzechV013
DonutInvoiceCzechV013 is a image-text-to-text model from TomasFAV. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
DonutInvoiceCzechV013
This model is a fine-tuned version of TomasFAV/DonutInvoiceCzechV01 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2355
- Accuracy: 0.9150
- F1: 0.9043
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: 9e-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2561 | 1.0 | 46 | 0.1958 | 0.8819 | 0.8581 |
| 0.1479 | 2.0 | 92 | 0.1839 | 0.9026 | 0.8821 |
| 0.0730 | 3.0 | 138 | 0.1941 | 0.9106 | 0.8889 |
| 0.0482 | 4.0 | 184 | 0.2087 | 0.9053 | 0.8872 |
| 0.0209 | 5.0 | 230 | 0.2163 | 0.8984 | 0.8691 |
| 0.0270 | 6.0 | 276 | 0.2235 | 0.9172 | 0.8821 |
| 0.0131 | 7.0 | 322 | 0.2250 | 0.9142 | 0.8862 |
| 0.0361 | 8.0 | 368 | 0.2241 | 0.9129 | 0.8849 |
| 0.0087 | 9.0 | 414 | 0.2465 | 0.9170 | 0.8906 |
| 0.0188 | 10.0 | 460 | 0.2351 | 0.9108 | 0.8855 |
| 0.0092 | 11.0 | 506 | 0.2228 | 0.9138 | 0.8889 |
| 0.0059 | 12.0 | 552 | 0.2324 | 0.9175 | 0.8974 |
| 0.0010 | 13.0 | 598 | 0.2355 | 0.9150 | 0.9043 |
| 0.0024 | 14.0 | 644 | 0.2377 | 0.9208 | 0.8991 |
| 0.0013 | 15.0 | 690 | 0.2408 | 0.9183 | 0.8974 |
| 0.0007 | 16.0 | 736 | 0.2449 | 0.9094 | 0.8906 |
| 0.0019 | 17.0 | 782 | 0.2480 | 0.9159 | 0.8991 |
| 0.0004 | 18.0 | 828 | 0.2466 | 0.9110 | 0.8906 |
| 0.0004 | 19.0 | 874 | 0.2475 | 0.9126 | 0.8923 |
| 0.0006 | 20.0 | 920 | 0.2474 | 0.9130 | 0.8923 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- vision-encoder-decoder
- License
- mit
- Created
- Mar 22, 2026
- Updated
- Apr 19, 2026