End of training

README.md

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+---
+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

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preprocessor_config.json

@@ -1,5 +1,5 @@
 {
-  "apply_ocr": false,
+  "apply_ocr": true,
   "do_normalize": true,
   "do_rescale": true,
   "do_resize": true,