---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- f1
- recall
- precision
model-index:
- name: Layoutv3test
  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. -->

# Layoutv3test

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9405
- F1: 0.7563
- Recall: 0.6959
- Precision: 0.8281
- Pred Bestellnummer: 146
- Percentage Pred Act Bestellnummer: 1.0210
- Pred Kundennr.: 57
- Percentage Pred Act Kundennr.: 1.1875
- Pred Bezug 1: 35
- Percentage Pred Act Bezug 1: 2.5
- Pred Modell 1: 114
- Percentage Pred Act Modell 1: 1.1515
- Pred Menge1: 74
- Percentage Pred Act Menge1: 3.5238
- Pred Möbelhaus: 93
- Percentage Pred Act Möbelhaus: 1.0220
- Pred Termin kundenwunsch - kw: 30
- Percentage Pred Act Termin kundenwunsch - kw: 0.9375
- Pred Kommission: 60
- Percentage Pred Act Kommission: 1.0345
- Pred Holz 1: 14
- Percentage Pred Act Holz 1: 0.7368
- Pred Modell 2: 57
- Percentage Pred Act Modell 2: 0.9194
- Pred Zusatz 1: 11
- Percentage Pred Act Zusatz 1: 0.7857
- Pred Holz 2: 39
- Percentage Pred Act Holz 2: 1.8571
- Pred Modell 3: 72
- Percentage Pred Act Modell 3: 1.0909
- Pred Var-ausf 1: 6
- Percentage Pred Act Var-ausf 1: 0.75
- Pred Menge3: 1
- Percentage Pred Act Menge3: 0.0455
- Act Bestellnummer: 143
- Act Kundennr.: 48
- Act Bezug 1: 14
- Act Modell 1: 99
- Act Menge1: 21
- Act Menge4: 10
- Act Möbelhaus: 91
- Act Bezug 2: 13
- Act Zusatz 2: 1
- Act Termin kundenwunsch - kw: 32
- Act Kommission: 58
- Act Holz 1: 19
- Act Menge3: 22
- Act Modell 2: 62
- Act Modell 3: 66
- Act Modell 4: 6
- Act Bezug 4: 7
- Act Zusatz 3: 1
- Act Holz 2: 21
- Act Menge2: 18
- Act Bezug 3: 4
- Act Var-ausf 1: 8
- Act Holz 3: 5
- Act Zusatz 1: 14
- Act Var-ausf. 2: 7
- Act Var-ausf. 3: 4
- Act Pv 3: 1
- Act Holz 4: 1
- Act Var-ausf. 5: 1
- Act Modell 5: 5
- Act La-anschrift: 6
- Act Menge5: 1

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.52.4
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1