---
library_name: transformers
license: mit
base_model: TomasFAV/DonutInvoiceCzechV01
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: DonutInvoiceCzechV013R
  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. -->

# DonutInvoiceCzechV013

This model is a fine-tuned version of [TomasFAV/DonutInvoiceCzechV01](https://huggingface.co/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