---
library_name: transformers
license: apache-2.0
base_model: TomasFAV/BERTInvoiceCzechV012
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERTInvoiceCzechV0123Test
  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. -->

# BERTInvoiceCzechV0123Test

This model is a fine-tuned version of [TomasFAV/BERTInvoiceCzechV012](https://huggingface.co/TomasFAV/BERTInvoiceCzechV012) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0612
- Precision: 0.8944
- Recall: 0.9177
- F1: 0.9059
- Accuracy: 0.9856

## 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   | 0.1056          | 0.7803    | 0.84   | 0.8091 | 0.9716   |
| No log        | 2.0   | 40   | 0.0831          | 0.8105    | 0.8901 | 0.8484 | 0.9764   |
| No log        | 3.0   | 60   | 0.0704          | 0.8410    | 0.8994 | 0.8692 | 0.9804   |
| No log        | 4.0   | 80   | 0.0675          | 0.8403    | 0.9095 | 0.8736 | 0.9808   |
| No log        | 5.0   | 100  | 0.0632          | 0.8630    | 0.8932 | 0.8779 | 0.9821   |
| No log        | 6.0   | 120  | 0.0706          | 0.8319    | 0.9111 | 0.8697 | 0.9800   |
| No log        | 7.0   | 140  | 0.0611          | 0.8729    | 0.8932 | 0.8829 | 0.9834   |
| No log        | 8.0   | 160  | 0.0608          | 0.8754    | 0.9056 | 0.8902 | 0.9835   |
| No log        | 9.0   | 180  | 0.0595          | 0.8769    | 0.9243 | 0.9000 | 0.9848   |
| No log        | 10.0  | 200  | 0.0606          | 0.8759    | 0.9153 | 0.8952 | 0.9842   |
| No log        | 11.0  | 220  | 0.0610          | 0.8855    | 0.9192 | 0.9021 | 0.9850   |
| No log        | 12.0  | 240  | 0.0632          | 0.8720    | 0.9258 | 0.8981 | 0.9844   |
| No log        | 13.0  | 260  | 0.0608          | 0.8961    | 0.9115 | 0.9037 | 0.9853   |
| No log        | 14.0  | 280  | 0.0610          | 0.8953    | 0.9165 | 0.9058 | 0.9855   |
| No log        | 15.0  | 300  | 0.0615          | 0.8874    | 0.9181 | 0.9025 | 0.9853   |
| No log        | 16.0  | 320  | 0.0627          | 0.8841    | 0.9216 | 0.9025 | 0.9851   |
| No log        | 17.0  | 340  | 0.0625          | 0.8807    | 0.92   | 0.8999 | 0.9847   |
| No log        | 18.0  | 360  | 0.0612          | 0.8944    | 0.9177 | 0.9059 | 0.9856   |
| No log        | 19.0  | 380  | 0.0619          | 0.8893    | 0.92   | 0.9044 | 0.9854   |
| No log        | 20.0  | 400  | 0.0618          | 0.8901    | 0.9212 | 0.9053 | 0.9856   |


### Framework versions

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