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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
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