---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: TomasFAV/Layoutlmv3InvoiceCzechV012
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Layoutlmv3InvoiceCzechV0123Test
  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. -->

# Layoutlmv3InvoiceCzechV0123Test

This model is a fine-tuned version of [TomasFAV/Layoutlmv3InvoiceCzechV012](https://huggingface.co/TomasFAV/Layoutlmv3InvoiceCzechV012) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0422
- Precision: 0.9203
- Recall: 0.9374
- F1: 0.9288
- Accuracy: 0.9928

## 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   | 0.0638          | 0.8128    | 0.8376 | 0.825  | 0.9834   |
| No log        | 2.0   | 46   | 0.0494          | 0.8666    | 0.8680 | 0.8673 | 0.9874   |
| No log        | 3.0   | 69   | 0.0400          | 0.8876    | 0.8951 | 0.8913 | 0.9905   |
| No log        | 4.0   | 92   | 0.0338          | 0.9048    | 0.9323 | 0.9183 | 0.9926   |
| No log        | 5.0   | 115  | 0.0362          | 0.9021    | 0.9357 | 0.9186 | 0.9924   |
| No log        | 6.0   | 138  | 0.0365          | 0.9150    | 0.9103 | 0.9126 | 0.9922   |
| No log        | 7.0   | 161  | 0.0382          | 0.9026    | 0.9408 | 0.9213 | 0.9923   |
| No log        | 8.0   | 184  | 0.0404          | 0.9003    | 0.9171 | 0.9086 | 0.9922   |
| No log        | 9.0   | 207  | 0.0375          | 0.9121    | 0.9306 | 0.9213 | 0.9925   |
| No log        | 10.0  | 230  | 0.0439          | 0.9115    | 0.9239 | 0.9176 | 0.9921   |
| No log        | 11.0  | 253  | 0.0399          | 0.8961    | 0.9340 | 0.9147 | 0.9918   |
| No log        | 12.0  | 276  | 0.0424          | 0.9153    | 0.9323 | 0.9237 | 0.9926   |
| No log        | 13.0  | 299  | 0.0429          | 0.9091    | 0.9137 | 0.9114 | 0.9922   |
| No log        | 14.0  | 322  | 0.0434          | 0.9274    | 0.9289 | 0.9281 | 0.9925   |
| No log        | 15.0  | 345  | 0.0433          | 0.9193    | 0.9255 | 0.9224 | 0.9925   |
| No log        | 16.0  | 368  | 0.0440          | 0.9174    | 0.9205 | 0.9189 | 0.9923   |
| No log        | 17.0  | 391  | 0.0422          | 0.9203    | 0.9374 | 0.9288 | 0.9928   |
| No log        | 18.0  | 414  | 0.0429          | 0.9138    | 0.9323 | 0.9229 | 0.9925   |
| No log        | 19.0  | 437  | 0.0434          | 0.9164    | 0.9272 | 0.9218 | 0.9925   |
| No log        | 20.0  | 460  | 0.0430          | 0.9133    | 0.9272 | 0.9202 | 0.9924   |


### Framework versions

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