---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERTInvoiceCzech
  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. -->

# BERTInvoiceCzech

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0222
- Precision: 0.9591
- Recall: 0.9633
- F1: 0.9612
- Accuracy: 0.9929

## 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_ratio: 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   | 42   | 1.2228          | 0.0       | 0.0    | 0.0    | 0.7831   |
| No log        | 2.0   | 84   | 0.5729          | 0.4183    | 0.4014 | 0.4097 | 0.8535   |
| No log        | 3.0   | 126  | 0.3043          | 0.6654    | 0.6861 | 0.6756 | 0.9155   |
| No log        | 4.0   | 168  | 0.2019          | 0.7618    | 0.7872 | 0.7743 | 0.9406   |
| No log        | 5.0   | 210  | 0.1278          | 0.8161    | 0.8587 | 0.8369 | 0.9627   |
| No log        | 6.0   | 252  | 0.0823          | 0.8727    | 0.9063 | 0.8892 | 0.9762   |
| No log        | 7.0   | 294  | 0.0599          | 0.9086    | 0.9284 | 0.9184 | 0.9824   |
| No log        | 8.0   | 336  | 0.0451          | 0.9335    | 0.9484 | 0.9409 | 0.9864   |
| No log        | 9.0   | 378  | 0.0373          | 0.9388    | 0.9499 | 0.9443 | 0.9877   |
| No log        | 10.0  | 420  | 0.0323          | 0.9458    | 0.9558 | 0.9508 | 0.9897   |
| No log        | 11.0  | 462  | 0.0283          | 0.9506    | 0.9580 | 0.9543 | 0.9914   |
| 0.4073        | 12.0  | 504  | 0.0277          | 0.9567    | 0.9620 | 0.9594 | 0.9920   |
| 0.4073        | 13.0  | 546  | 0.0243          | 0.9517    | 0.9568 | 0.9542 | 0.9916   |
| 0.4073        | 14.0  | 588  | 0.0256          | 0.9610    | 0.9661 | 0.9635 | 0.9928   |
| 0.4073        | 15.0  | 630  | 0.0245          | 0.9588    | 0.9633 | 0.9610 | 0.9927   |
| 0.4073        | 16.0  | 672  | 0.0231          | 0.9606    | 0.9636 | 0.9621 | 0.9930   |
| 0.4073        | 17.0  | 714  | 0.0239          | 0.9582    | 0.9627 | 0.9604 | 0.9925   |
| 0.4073        | 18.0  | 756  | 0.0221          | 0.9606    | 0.9642 | 0.9624 | 0.9931   |
| 0.4073        | 19.0  | 798  | 0.0222          | 0.9594    | 0.9639 | 0.9617 | 0.9930   |
| 0.4073        | 20.0  | 840  | 0.0222          | 0.9591    | 0.9633 | 0.9612 | 0.9929   |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2