---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: TomasFAV/Layoutlmv3InvoiceCzechV01
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Layoutlmv3InvoiceCzechV013
  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. -->

# Layoutlmv3InvoiceCzechV013

This model is a fine-tuned version of [TomasFAV/Layoutlmv3InvoiceCzechV01](https://huggingface.co/TomasFAV/Layoutlmv3InvoiceCzechV01) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0405
- Precision: 0.9167
- Recall: 0.9306
- F1: 0.9236
- Accuracy: 0.9925

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 23   | 0.0980          | 0.7728    | 0.7022 | 0.7358 | 0.9754   |
| No log        | 2.0   | 46   | 0.0724          | 0.7531    | 0.8308 | 0.7900 | 0.9796   |
| No log        | 3.0   | 69   | 0.0544          | 0.8523    | 0.8494 | 0.8508 | 0.9877   |
| No log        | 4.0   | 92   | 0.0465          | 0.8307    | 0.9052 | 0.8664 | 0.9881   |
| No log        | 5.0   | 115  | 0.0447          | 0.8613    | 0.9036 | 0.8819 | 0.9896   |
| No log        | 6.0   | 138  | 0.0478          | 0.8941    | 0.9002 | 0.8971 | 0.9907   |
| No log        | 7.0   | 161  | 0.0400          | 0.8911    | 0.9137 | 0.9023 | 0.9911   |
| No log        | 8.0   | 184  | 0.0409          | 0.9064    | 0.9171 | 0.9117 | 0.9925   |
| No log        | 9.0   | 207  | 0.0410          | 0.9037    | 0.9205 | 0.9120 | 0.9919   |
| No log        | 10.0  | 230  | 0.0432          | 0.8805    | 0.9222 | 0.9008 | 0.9910   |
| No log        | 11.0  | 253  | 0.0396          | 0.9039    | 0.9391 | 0.9212 | 0.9926   |
| No log        | 12.0  | 276  | 0.0406          | 0.9128    | 0.9205 | 0.9166 | 0.9923   |
| No log        | 13.0  | 299  | 0.0380          | 0.9117    | 0.9255 | 0.9186 | 0.9927   |
| No log        | 14.0  | 322  | 0.0391          | 0.9064    | 0.9340 | 0.9200 | 0.9926   |
| No log        | 15.0  | 345  | 0.0393          | 0.9066    | 0.9357 | 0.9209 | 0.9926   |
| No log        | 16.0  | 368  | 0.0416          | 0.9176    | 0.9239 | 0.9207 | 0.9924   |
| No log        | 17.0  | 391  | 0.0382          | 0.9097    | 0.9374 | 0.9233 | 0.9928   |
| No log        | 18.0  | 414  | 0.0405          | 0.9183    | 0.9323 | 0.9253 | 0.9926   |
| No log        | 19.0  | 437  | 0.0402          | 0.9165    | 0.9289 | 0.9227 | 0.9927   |
| No log        | 20.0  | 460  | 0.0398          | 0.9147    | 0.9255 | 0.9201 | 0.9925   |


### Framework versions

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