---
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: BERTInvoiceCzechV3
  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. -->

# BERTInvoiceCzechV3

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: 0.0873
- Precision: 0.8287
- Recall: 0.8718
- F1: 0.8497
- Accuracy: 0.9790

## 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: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 20   | 2.6840          | 0.0071    | 0.0194 | 0.0103 | 0.6810   |
| No log        | 2.0   | 40   | 0.6125          | 0.0       | 0.0    | 0.0    | 0.9123   |
| No log        | 3.0   | 60   | 0.4626          | 0.0       | 0.0    | 0.0    | 0.9123   |
| No log        | 4.0   | 80   | 0.3490          | 0.3419    | 0.1239 | 0.1819 | 0.9169   |
| No log        | 5.0   | 100  | 0.2754          | 0.3776    | 0.2893 | 0.3276 | 0.9278   |
| No log        | 6.0   | 120  | 0.2266          | 0.4686    | 0.4171 | 0.4413 | 0.9389   |
| No log        | 7.0   | 140  | 0.1828          | 0.5234    | 0.4870 | 0.5045 | 0.9466   |
| No log        | 8.0   | 160  | 0.1729          | 0.5567    | 0.5433 | 0.5499 | 0.9495   |
| No log        | 9.0   | 180  | 0.1619          | 0.5477    | 0.5577 | 0.5526 | 0.9495   |
| No log        | 10.0  | 200  | 0.1462          | 0.5730    | 0.5565 | 0.5646 | 0.9519   |
| No log        | 11.0  | 220  | 0.1457          | 0.6067    | 0.6159 | 0.6113 | 0.9531   |
| No log        | 12.0  | 240  | 0.1374          | 0.6406    | 0.6583 | 0.6493 | 0.9573   |
| No log        | 13.0  | 260  | 0.1224          | 0.6855    | 0.6882 | 0.6868 | 0.9624   |
| No log        | 14.0  | 280  | 0.1208          | 0.7253    | 0.7157 | 0.7205 | 0.9658   |
| No log        | 15.0  | 300  | 0.1127          | 0.7233    | 0.7107 | 0.7169 | 0.9656   |
| No log        | 16.0  | 320  | 0.1138          | 0.7535    | 0.7480 | 0.7507 | 0.9688   |
| No log        | 17.0  | 340  | 0.1128          | 0.7648    | 0.7639 | 0.7643 | 0.9697   |
| No log        | 18.0  | 360  | 0.1089          | 0.7688    | 0.7724 | 0.7706 | 0.9704   |
| No log        | 19.0  | 380  | 0.1033          | 0.7738    | 0.7903 | 0.7819 | 0.9707   |
| No log        | 20.0  | 400  | 0.0960          | 0.7982    | 0.8078 | 0.8029 | 0.9736   |
| No log        | 21.0  | 420  | 0.1022          | 0.7821    | 0.8252 | 0.8031 | 0.9726   |
| No log        | 22.0  | 440  | 0.0915          | 0.8092    | 0.8252 | 0.8172 | 0.9753   |
| No log        | 23.0  | 460  | 0.0901          | 0.8289    | 0.8353 | 0.8321 | 0.9773   |
| No log        | 24.0  | 480  | 0.0933          | 0.7954    | 0.8377 | 0.8160 | 0.9749   |
| 0.3542        | 25.0  | 500  | 0.0883          | 0.8093    | 0.8388 | 0.8238 | 0.9769   |
| 0.3542        | 26.0  | 520  | 0.0884          | 0.8282    | 0.8520 | 0.8400 | 0.9780   |
| 0.3542        | 27.0  | 540  | 0.0898          | 0.7909    | 0.8610 | 0.8245 | 0.9757   |
| 0.3542        | 28.0  | 560  | 0.0957          | 0.8004    | 0.8676 | 0.8327 | 0.9757   |
| 0.3542        | 29.0  | 580  | 0.0876          | 0.8253    | 0.8548 | 0.8398 | 0.9787   |
| 0.3542        | 30.0  | 600  | 0.0886          | 0.8257    | 0.8571 | 0.8411 | 0.9785   |
| 0.3542        | 31.0  | 620  | 0.0867          | 0.8286    | 0.8637 | 0.8458 | 0.9792   |
| 0.3542        | 32.0  | 640  | 0.0919          | 0.8132    | 0.8571 | 0.8346 | 0.9774   |
| 0.3542        | 33.0  | 660  | 0.0876          | 0.8239    | 0.8668 | 0.8448 | 0.9787   |
| 0.3542        | 34.0  | 680  | 0.0888          | 0.8219    | 0.8672 | 0.8439 | 0.9783   |
| 0.3542        | 35.0  | 700  | 0.0872          | 0.8315    | 0.8683 | 0.8495 | 0.9792   |
| 0.3542        | 36.0  | 720  | 0.0872          | 0.8287    | 0.8718 | 0.8497 | 0.9790   |
| 0.3542        | 37.0  | 740  | 0.0881          | 0.8259    | 0.8715 | 0.8481 | 0.9788   |
| 0.3542        | 38.0  | 760  | 0.0899          | 0.8199    | 0.8699 | 0.8442 | 0.9781   |
| 0.3542        | 39.0  | 780  | 0.0892          | 0.8264    | 0.8687 | 0.8470 | 0.9786   |
| 0.3542        | 40.0  | 800  | 0.0896          | 0.8246    | 0.8691 | 0.8463 | 0.9785   |


### Framework versions

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