---
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: Layoutlmv3InvoiceCzech
  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. -->

# Layoutlmv3InvoiceCzech

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: 0.0649
- Precision: 0.8992
- Recall: 0.9155
- F1: 0.9072
- Accuracy: 0.9862

## 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: 16
- eval_batch_size: 2
- 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_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 43   | 1.5391          | 0.0       | 0.0    | 0.0    | 0.8323   |
| No log        | 2.0   | 86   | 1.0087          | 0.0       | 0.0    | 0.0    | 0.8323   |
| No log        | 3.0   | 129  | 0.6795          | 0.0739    | 0.0338 | 0.0464 | 0.8375   |
| No log        | 4.0   | 172  | 0.5549          | 0.2447    | 0.2802 | 0.2613 | 0.8690   |
| No log        | 5.0   | 215  | 0.4249          | 0.4758    | 0.5821 | 0.5236 | 0.9183   |
| No log        | 6.0   | 258  | 0.3194          | 0.5484    | 0.6836 | 0.6086 | 0.9374   |
| No log        | 7.0   | 301  | 0.2431          | 0.6235    | 0.7379 | 0.6759 | 0.9502   |
| No log        | 8.0   | 344  | 0.1812          | 0.7525    | 0.8116 | 0.7809 | 0.9673   |
| No log        | 9.0   | 387  | 0.1548          | 0.7991    | 0.8357 | 0.8170 | 0.9705   |
| No log        | 10.0  | 430  | 0.1248          | 0.8182    | 0.8478 | 0.8327 | 0.9758   |
| No log        | 11.0  | 473  | 0.1104          | 0.8451    | 0.8696 | 0.8571 | 0.9786   |
| 0.64          | 12.0  | 516  | 0.0965          | 0.8506    | 0.8732 | 0.8617 | 0.9804   |
| 0.64          | 13.0  | 559  | 0.0909          | 0.8688    | 0.8877 | 0.8781 | 0.9820   |
| 0.64          | 14.0  | 602  | 0.0819          | 0.8826    | 0.8986 | 0.8905 | 0.9837   |
| 0.64          | 15.0  | 645  | 0.0779          | 0.8897    | 0.9058 | 0.8977 | 0.9850   |
| 0.64          | 16.0  | 688  | 0.0734          | 0.8942    | 0.9082 | 0.9011 | 0.9852   |
| 0.64          | 17.0  | 731  | 0.0700          | 0.8955    | 0.9106 | 0.9030 | 0.9856   |
| 0.64          | 18.0  | 774  | 0.0666          | 0.8988    | 0.9118 | 0.9053 | 0.9861   |
| 0.64          | 19.0  | 817  | 0.0655          | 0.8992    | 0.9155 | 0.9072 | 0.9862   |
| 0.64          | 20.0  | 860  | 0.0649          | 0.8992    | 0.9155 | 0.9072 | 0.9862   |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2