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layoutlmv3-invoice

Token Classification
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layoutlmv3
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layoutlmv3-invoice

This model is a fine-tuned version of microsoft/layoutlmv3-base on the layoutlmv3 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1889
  • Precision: 0.9698
  • Recall: 0.9592
  • F1: 0.9645
  • Accuracy: 0.9708

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 3500

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 5.32 250 0.3826 0.9471 0.9278 0.9374 0.9465
0.8433 10.64 500 0.1720 0.9697 0.9560 0.9628 0.9684
0.8433 15.96 750 0.1631 0.9714 0.9608 0.9661 0.9684
0.0347 21.28 1000 0.1548 0.9746 0.9639 0.9692 0.9733
0.0347 26.6 1250 0.1700 0.9698 0.9576 0.9637 0.9672
0.0116 31.91 1500 0.1812 0.9667 0.9576 0.9621 0.9648
0.0116 37.23 1750 0.1513 0.9683 0.9592 0.9637 0.9721
0.0066 42.55 2000 0.1555 0.9730 0.9623 0.9676 0.9757
0.0066 47.87 2250 0.1729 0.9714 0.9592 0.9652 0.9708
0.0048 53.19 2500 0.1854 0.9761 0.9623 0.9692 0.9721
0.0048 58.51 2750 0.1863 0.9714 0.9592 0.9652 0.9696
0.0037 63.83 3000 0.1813 0.9761 0.9623 0.9692 0.9733
0.0037 69.15 3250 0.1903 0.9698 0.9592 0.9645 0.9708
0.0034 74.47 3500 0.1889 0.9698 0.9592 0.9645 0.9708

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Base model

microsoft/layoutlmv3-base
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Evaluation results

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