---
library_name: transformers
license: mit
base_model: naver-clova-ix/donut-base-finetuned-cord-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: DonutInvoiceCzechV3
  results: []
---

<!-- 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. -->

# DonutInvoiceCzechV3

This model is a fine-tuned version of [naver-clova-ix/donut-base-finetuned-cord-v2](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2946
- Accuracy: 0.9152
- F1: 0.8838

## 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: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 3.9346        | 1.0   | 46   | 2.6485          | 0.0116   | 0.0064 |
| 1.3843        | 2.0   | 92   | 1.2891          | 0.2501   | 0.2407 |
| 0.8102        | 3.0   | 138  | 0.7001          | 0.5997   | 0.5336 |
| 0.2805        | 4.0   | 184  | 0.4553          | 0.6544   | 0.6571 |
| 0.1336        | 5.0   | 230  | 0.3413          | 0.8010   | 0.7771 |
| 0.1062        | 6.0   | 276  | 0.2924          | 0.7955   | 0.7831 |
| 0.0869        | 7.0   | 322  | 0.2980          | 0.8219   | 0.7988 |
| 0.0957        | 8.0   | 368  | 0.3558          | 0.8100   | 0.7938 |
| 0.0704        | 9.0   | 414  | 0.3160          | 0.8147   | 0.8055 |
| 0.0674        | 10.0  | 460  | 0.3314          | 0.8531   | 0.8247 |
| 0.0464        | 11.0  | 506  | 0.3728          | 0.8521   | 0.8146 |
| 0.0358        | 12.0  | 552  | 0.3211          | 0.8372   | 0.8079 |
| 0.0222        | 13.0  | 598  | 0.3009          | 0.8836   | 0.8420 |
| 0.0299        | 14.0  | 644  | 0.2888          | 0.8698   | 0.8362 |
| 0.0133        | 15.0  | 690  | 0.3496          | 0.8558   | 0.8459 |
| 0.0201        | 16.0  | 736  | 0.2847          | 0.8961   | 0.8665 |
| 0.0142        | 17.0  | 782  | 0.3228          | 0.9005   | 0.8652 |
| 0.0163        | 18.0  | 828  | 0.3359          | 0.8669   | 0.8310 |
| 0.0096        | 19.0  | 874  | 0.3167          | 0.8759   | 0.8488 |
| 0.0175        | 20.0  | 920  | 0.2905          | 0.8938   | 0.8687 |
| 0.0129        | 21.0  | 966  | 0.3119          | 0.8797   | 0.8570 |
| 0.0081        | 22.0  | 1012 | 0.3157          | 0.8780   | 0.8729 |
| 0.0036        | 23.0  | 1058 | 0.2950          | 0.9029   | 0.8731 |
| 0.0049        | 24.0  | 1104 | 0.3194          | 0.9048   | 0.8632 |
| 0.0034        | 25.0  | 1150 | 0.3091          | 0.8987   | 0.8650 |
| 0.0012        | 26.0  | 1196 | 0.2910          | 0.8968   | 0.8718 |
| 0.0049        | 27.0  | 1242 | 0.2924          | 0.9115   | 0.8769 |
| 0.0025        | 28.0  | 1288 | 0.2939          | 0.9040   | 0.8679 |
| 0.0014        | 29.0  | 1334 | 0.2946          | 0.9152   | 0.8838 |
| 0.0014        | 30.0  | 1380 | 0.3091          | 0.8989   | 0.8676 |
| 0.0004        | 31.0  | 1426 | 0.2930          | 0.8991   | 0.8637 |
| 0.0005        | 32.0  | 1472 | 0.2962          | 0.8977   | 0.8747 |
| 0.0008        | 33.0  | 1518 | 0.2922          | 0.8974   | 0.8665 |
| 0.0004        | 34.0  | 1564 | 0.2875          | 0.8982   | 0.8696 |
| 0.0004        | 35.0  | 1610 | 0.2895          | 0.8962   | 0.8665 |
| 0.0042        | 36.0  | 1656 | 0.2877          | 0.8944   | 0.8665 |
| 0.0004        | 37.0  | 1702 | 0.2879          | 0.8965   | 0.8701 |
| 0.0003        | 38.0  | 1748 | 0.2875          | 0.8984   | 0.8718 |
| 0.0003        | 39.0  | 1794 | 0.2879          | 0.8984   | 0.8718 |
| 0.0004        | 40.0  | 1840 | 0.2874          | 0.8984   | 0.8718 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2