---
library_name: transformers
license: apache-2.0
base_model: TomasFAV/BERTInvoiceCzechV0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERTInvoiceCzechV03
  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. -->

# BERTInvoiceCzechV03

This model is a fine-tuned version of [TomasFAV/BERTInvoiceCzechV0](https://huggingface.co/TomasFAV/BERTInvoiceCzechV0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0683
- Precision: 0.8635
- Recall: 0.8866
- F1: 0.8749
- Accuracy: 0.9833

## 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   | 0.1657          | 0.6566    | 0.7456 | 0.6983 | 0.9547   |
| No log        | 2.0   | 40   | 0.1222          | 0.7308    | 0.7821 | 0.7556 | 0.9653   |
| No log        | 3.0   | 60   | 0.1044          | 0.7512    | 0.8233 | 0.7856 | 0.9707   |
| No log        | 4.0   | 80   | 0.0872          | 0.7799    | 0.8532 | 0.8149 | 0.9747   |
| No log        | 5.0   | 100  | 0.0897          | 0.7791    | 0.8808 | 0.8268 | 0.9748   |
| No log        | 6.0   | 120  | 0.0850          | 0.7725    | 0.8730 | 0.8197 | 0.9742   |
| No log        | 7.0   | 140  | 0.0704          | 0.8433    | 0.88   | 0.8613 | 0.9812   |
| No log        | 8.0   | 160  | 0.0749          | 0.8291    | 0.8649 | 0.8466 | 0.9799   |
| No log        | 9.0   | 180  | 0.0752          | 0.8187    | 0.8753 | 0.8461 | 0.9794   |
| No log        | 10.0  | 200  | 0.0687          | 0.8440    | 0.8761 | 0.8598 | 0.9815   |
| No log        | 11.0  | 220  | 0.0671          | 0.8436    | 0.8816 | 0.8621 | 0.9820   |
| No log        | 12.0  | 240  | 0.0711          | 0.8376    | 0.8913 | 0.8636 | 0.9809   |
| No log        | 13.0  | 260  | 0.0683          | 0.8638    | 0.8870 | 0.8753 | 0.9833   |
| No log        | 14.0  | 280  | 0.0686          | 0.8488    | 0.8870 | 0.8675 | 0.9818   |
| No log        | 15.0  | 300  | 0.0690          | 0.8439    | 0.8816 | 0.8623 | 0.9816   |
| No log        | 16.0  | 320  | 0.0669          | 0.8469    | 0.8827 | 0.8644 | 0.9819   |
| No log        | 17.0  | 340  | 0.0699          | 0.8404    | 0.8897 | 0.8644 | 0.9814   |
| No log        | 18.0  | 360  | 0.0684          | 0.8532    | 0.8870 | 0.8698 | 0.9825   |
| No log        | 19.0  | 380  | 0.0701          | 0.8408    | 0.8920 | 0.8656 | 0.9815   |
| No log        | 20.0  | 400  | 0.0685          | 0.8560    | 0.8909 | 0.8731 | 0.9827   |


### Framework versions

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