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

  • Loss: 0.6194
  • Precision: 0.9002
  • Recall: 0.9101
  • F1: 0.9051
  • Accuracy: 0.8547

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.33 100 0.6953 0.7761 0.8058 0.7906 0.7680
No log 2.67 200 0.5117 0.8250 0.8808 0.8520 0.8290
No log 4.0 300 0.5177 0.8397 0.8897 0.8640 0.8337
No log 5.33 400 0.5165 0.8642 0.9106 0.8868 0.8509
0.5653 6.67 500 0.5378 0.8735 0.9091 0.8909 0.8458
0.5653 8.0 600 0.5698 0.8733 0.9111 0.8918 0.8482
0.5653 9.33 700 0.5773 0.8934 0.9076 0.9004 0.8557
0.5653 10.67 800 0.6073 0.8905 0.9006 0.8955 0.8520
0.5653 12.0 900 0.6090 0.8940 0.9091 0.9015 0.8513
0.1357 13.33 1000 0.6194 0.9002 0.9101 0.9051 0.8547

Framework versions

  • Transformers 4.33.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Evaluation results