---
library_name: transformers
license: mit
base_model: microsoft/table-transformer-detection
tags:
- generated_from_trainer
model-index:
- name: DertInvoiceCzech
  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. -->

# DertInvoiceCzech

This model is a fine-tuned version of [microsoft/table-transformer-detection](https://huggingface.co/microsoft/table-transformer-detection) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 6.0877

## 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: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 38   | 8.9100          |
| No log        | 2.0   | 76   | 8.6387          |
| No log        | 3.0   | 114  | 8.2508          |
| No log        | 4.0   | 152  | 7.7641          |
| No log        | 5.0   | 190  | 7.2348          |
| No log        | 6.0   | 228  | 7.0283          |
| No log        | 7.0   | 266  | 6.8791          |
| No log        | 8.0   | 304  | 6.7655          |
| No log        | 9.0   | 342  | 6.6748          |
| No log        | 10.0  | 380  | 6.6063          |
| No log        | 11.0  | 418  | 6.5481          |
| No log        | 12.0  | 456  | 6.4950          |
| No log        | 13.0  | 494  | 6.4460          |
| 7.372         | 14.0  | 532  | 6.4030          |
| 7.372         | 15.0  | 570  | 6.3710          |
| 7.372         | 16.0  | 608  | 6.3404          |
| 7.372         | 17.0  | 646  | 6.3093          |
| 7.372         | 18.0  | 684  | 6.2916          |
| 7.372         | 19.0  | 722  | 6.2786          |
| 7.372         | 20.0  | 760  | 6.2660          |
| 7.372         | 21.0  | 798  | 6.2440          |
| 7.372         | 22.0  | 836  | 6.2129          |
| 7.372         | 23.0  | 874  | 6.2026          |
| 7.372         | 24.0  | 912  | 6.1897          |
| 7.372         | 25.0  | 950  | 6.1778          |
| 7.372         | 26.0  | 988  | 6.1668          |
| 6.3365        | 27.0  | 1026 | 6.1562          |
| 6.3365        | 28.0  | 1064 | 6.1451          |
| 6.3365        | 29.0  | 1102 | 6.1313          |
| 6.3365        | 30.0  | 1140 | 6.1220          |
| 6.3365        | 31.0  | 1178 | 6.1164          |
| 6.3365        | 32.0  | 1216 | 6.1105          |
| 6.3365        | 33.0  | 1254 | 6.1038          |
| 6.3365        | 34.0  | 1292 | 6.1002          |
| 6.3365        | 35.0  | 1330 | 6.0966          |
| 6.3365        | 36.0  | 1368 | 6.0935          |
| 6.3365        | 37.0  | 1406 | 6.0926          |
| 6.3365        | 38.0  | 1444 | 6.0905          |
| 6.3365        | 39.0  | 1482 | 6.0892          |
| 6.1779        | 40.0  | 1520 | 6.0877          |


### Framework versions

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