---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Layoutlmv3InvoiceCzechV3
  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. -->

# Layoutlmv3InvoiceCzechV3

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0874
- Precision: 0.6694
- Recall: 0.6920
- F1: 0.6805
- Accuracy: 0.9804

## 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: 1e-05
- train_batch_size: 8
- 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
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 23   | 2.5446          | 0.0       | 0.0    | 0.0    | 0.9472   |
| No log        | 2.0   | 46   | 0.8320          | 0.0       | 0.0    | 0.0    | 0.9473   |
| No log        | 3.0   | 69   | 0.4185          | 0.0       | 0.0    | 0.0    | 0.9473   |
| No log        | 4.0   | 92   | 0.3832          | 0.0       | 0.0    | 0.0    | 0.9473   |
| No log        | 5.0   | 115  | 0.2963          | 0.0       | 0.0    | 0.0    | 0.9473   |
| No log        | 6.0   | 138  | 0.2591          | 0.0357    | 0.0017 | 0.0032 | 0.9473   |
| No log        | 7.0   | 161  | 0.2357          | 0.2468    | 0.1320 | 0.1720 | 0.9510   |
| No log        | 8.0   | 184  | 0.2226          | 0.4192    | 0.2589 | 0.3201 | 0.9574   |
| No log        | 9.0   | 207  | 0.2062          | 0.5011    | 0.3875 | 0.4370 | 0.9633   |
| No log        | 10.0  | 230  | 0.1946          | 0.5164    | 0.4264 | 0.4671 | 0.9651   |
| No log        | 11.0  | 253  | 0.1839          | 0.5515    | 0.4349 | 0.4863 | 0.9663   |
| No log        | 12.0  | 276  | 0.1724          | 0.5376    | 0.4839 | 0.5093 | 0.9677   |
| No log        | 13.0  | 299  | 0.1675          | 0.5824    | 0.5381 | 0.5594 | 0.9699   |
| No log        | 14.0  | 322  | 0.1569          | 0.6127    | 0.5567 | 0.5833 | 0.9709   |
| No log        | 15.0  | 345  | 0.1298          | 0.6084    | 0.5888 | 0.5985 | 0.9719   |
| No log        | 16.0  | 368  | 0.1226          | 0.5652    | 0.5939 | 0.5792 | 0.9729   |
| No log        | 17.0  | 391  | 0.1157          | 0.5621    | 0.5973 | 0.5792 | 0.9739   |
| No log        | 18.0  | 414  | 0.1148          | 0.5863    | 0.6210 | 0.6031 | 0.9757   |
| No log        | 19.0  | 437  | 0.1134          | 0.5974    | 0.6176 | 0.6073 | 0.9760   |
| No log        | 20.0  | 460  | 0.1093          | 0.5866    | 0.6244 | 0.6049 | 0.9757   |
| No log        | 21.0  | 483  | 0.1030          | 0.5953    | 0.6396 | 0.6166 | 0.9772   |
| 0.4082        | 22.0  | 506  | 0.1027          | 0.6025    | 0.6413 | 0.6213 | 0.9771   |
| 0.4082        | 23.0  | 529  | 0.1017          | 0.6093    | 0.6464 | 0.6273 | 0.9776   |
| 0.4082        | 24.0  | 552  | 0.1049          | 0.6104    | 0.6362 | 0.6230 | 0.9773   |
| 0.4082        | 25.0  | 575  | 0.0970          | 0.5913    | 0.6413 | 0.6153 | 0.9767   |
| 0.4082        | 26.0  | 598  | 0.0922          | 0.6069    | 0.6582 | 0.6315 | 0.9777   |
| 0.4082        | 27.0  | 621  | 0.0937          | 0.6154    | 0.6633 | 0.6384 | 0.9782   |
| 0.4082        | 28.0  | 644  | 0.0934          | 0.6266    | 0.6616 | 0.6436 | 0.9787   |
| 0.4082        | 29.0  | 667  | 0.0921          | 0.6177    | 0.6616 | 0.6389 | 0.9785   |
| 0.4082        | 30.0  | 690  | 0.0904          | 0.6109    | 0.6616 | 0.6353 | 0.9783   |
| 0.4082        | 31.0  | 713  | 0.0922          | 0.6194    | 0.6582 | 0.6382 | 0.9786   |
| 0.4082        | 32.0  | 736  | 0.0896          | 0.6304    | 0.6667 | 0.6480 | 0.9791   |
| 0.4082        | 33.0  | 759  | 0.0903          | 0.6314    | 0.6667 | 0.6486 | 0.9793   |
| 0.4082        | 34.0  | 782  | 0.0879          | 0.6377    | 0.6819 | 0.6590 | 0.9794   |
| 0.4082        | 35.0  | 805  | 0.0863          | 0.6439    | 0.6853 | 0.6639 | 0.9798   |
| 0.4082        | 36.0  | 828  | 0.0860          | 0.6421    | 0.6768 | 0.6590 | 0.9794   |
| 0.4082        | 37.0  | 851  | 0.0874          | 0.6721    | 0.6937 | 0.6828 | 0.9805   |
| 0.4082        | 38.0  | 874  | 0.0861          | 0.6559    | 0.6870 | 0.6711 | 0.9799   |
| 0.4082        | 39.0  | 897  | 0.0867          | 0.6694    | 0.6920 | 0.6805 | 0.9803   |
| 0.4082        | 40.0  | 920  | 0.0860          | 0.6667    | 0.6937 | 0.6799 | 0.9803   |


### Framework versions

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