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layoutlmv3-finetuned-cord

This model is a fine-tuned version of layoutlmv3 on the mp-02/cord dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1292
  • Precision: 0.9672
  • Recall: 0.9776
  • F1: 0.9724
  • Accuracy: 0.9767

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: 10
  • eval_batch_size: 10
  • 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 3.125 250 0.6018 0.8218 0.8633 0.8420 0.8577
1.0098 6.25 500 0.2695 0.9205 0.9495 0.9347 0.9451
1.0098 9.375 750 0.1813 0.9528 0.9693 0.9610 0.9639
0.1993 12.5 1000 0.1557 0.9616 0.9743 0.9679 0.9739
0.1993 15.625 1250 0.1749 0.9608 0.9743 0.9675 0.9703
0.0787 18.75 1500 0.1482 0.9616 0.9743 0.9679 0.9730
0.0787 21.875 1750 0.1288 0.9640 0.9751 0.9695 0.9762
0.0433 25.0 2000 0.1292 0.9672 0.9776 0.9724 0.9767
0.0433 28.125 2250 0.1372 0.9623 0.9735 0.9679 0.9735
0.031 31.25 2500 0.1408 0.9631 0.9743 0.9687 0.9730

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu118
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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Dataset used to train mp-02/layoutlmv3-finetuned-cord

Evaluation results