---
library_name: transformers
license: apache-2.0
base_model: TomasFAV/BERTInvoiceCzechV01
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERTInvoiceCzechV013
  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. -->

# BERTInvoiceCzechV013

This model is a fine-tuned version of [TomasFAV/BERTInvoiceCzechV01](https://huggingface.co/TomasFAV/BERTInvoiceCzechV01) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0656
- Precision: 0.8707
- Recall: 0.8816
- F1: 0.8761
- Accuracy: 0.9835

## 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_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   | 20   | 0.1306          | 0.7273    | 0.7581 | 0.7423 | 0.9645   |
| No log        | 2.0   | 40   | 0.1137          | 0.7402    | 0.8054 | 0.7714 | 0.9678   |
| No log        | 3.0   | 60   | 0.0909          | 0.7828    | 0.8369 | 0.8089 | 0.9740   |
| No log        | 4.0   | 80   | 0.0766          | 0.8162    | 0.8711 | 0.8428 | 0.9785   |
| No log        | 5.0   | 100  | 0.0761          | 0.8141    | 0.8858 | 0.8484 | 0.9784   |
| No log        | 6.0   | 120  | 0.0785          | 0.7960    | 0.8850 | 0.8382 | 0.9769   |
| No log        | 7.0   | 140  | 0.0662          | 0.8520    | 0.8722 | 0.8620 | 0.9817   |
| No log        | 8.0   | 160  | 0.0722          | 0.8378    | 0.8765 | 0.8567 | 0.9810   |
| No log        | 9.0   | 180  | 0.0712          | 0.8250    | 0.8827 | 0.8529 | 0.9801   |
| No log        | 10.0  | 200  | 0.0670          | 0.8544    | 0.8819 | 0.8680 | 0.9823   |
| No log        | 11.0  | 220  | 0.0663          | 0.8518    | 0.8909 | 0.8709 | 0.9828   |
| No log        | 12.0  | 240  | 0.0680          | 0.8341    | 0.8843 | 0.8584 | 0.9809   |
| No log        | 13.0  | 260  | 0.0656          | 0.8704    | 0.8816 | 0.8759 | 0.9835   |
| No log        | 14.0  | 280  | 0.0655          | 0.8566    | 0.8885 | 0.8723 | 0.9827   |
| No log        | 15.0  | 300  | 0.0659          | 0.8466    | 0.8831 | 0.8645 | 0.9822   |
| No log        | 16.0  | 320  | 0.0662          | 0.8483    | 0.8862 | 0.8669 | 0.9821   |
| No log        | 17.0  | 340  | 0.0689          | 0.8402    | 0.8885 | 0.8637 | 0.9815   |
| No log        | 18.0  | 360  | 0.0662          | 0.8566    | 0.8905 | 0.8732 | 0.9829   |
| No log        | 19.0  | 380  | 0.0670          | 0.8519    | 0.8893 | 0.8702 | 0.9824   |
| No log        | 20.0  | 400  | 0.0663          | 0.8541    | 0.8885 | 0.8710 | 0.9825   |


### Framework versions

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