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layoutlmv3-finetuned-cord_100

Token Classification
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layoutlmv3
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layoutlmv3-finetuned-cord_100

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

  • Loss: 0.7215
  • Precision: 0.8720
  • Recall: 0.8870
  • F1: 0.8794
  • Accuracy: 0.8790

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: 5
  • eval_batch_size: 5
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 2500

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 12.5 250 1.0892 0.7345 0.7867 0.7597 0.7806
1.3039 25.0 500 0.7150 0.8054 0.8428 0.8237 0.8281
1.3039 37.5 750 0.6320 0.8335 0.8615 0.8473 0.8540
0.2171 50.0 1000 0.6427 0.8651 0.8832 0.8741 0.8722
0.2171 62.5 1250 0.6640 0.8672 0.8847 0.8759 0.8765
0.0654 75.0 1500 0.6758 0.8650 0.8825 0.8737 0.8731
0.0654 87.5 1750 0.7028 0.8684 0.8840 0.8761 0.8765
0.0338 100.0 2000 0.7252 0.8710 0.8847 0.8778 0.8769
0.0338 112.5 2250 0.7227 0.8710 0.8847 0.8778 0.8778
0.0257 125.0 2500 0.7215 0.8720 0.8870 0.8794 0.8790

Framework versions

  • Transformers 4.21.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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Evaluation results

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