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---
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
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