layoutlmv3-funsd

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

  • Loss: 0.8428
  • Precision: 0.8993
  • Recall: 0.9046
  • F1: 0.9019
  • Accuracy: 0.8354

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 2.63 100 0.6294 0.7864 0.8286 0.8070 0.7966
No log 5.26 200 0.5034 0.8389 0.8793 0.8586 0.8343
No log 7.89 300 0.5673 0.8597 0.9011 0.8799 0.8416
No log 10.53 400 0.5730 0.8783 0.9106 0.8941 0.8395
0.4463 13.16 500 0.6630 0.8923 0.9016 0.8970 0.8412
0.4463 15.79 600 0.7048 0.8850 0.8947 0.8898 0.8329
0.4463 18.42 700 0.7772 0.8925 0.9071 0.8997 0.8317
0.4463 21.05 800 0.8408 0.8959 0.9016 0.8987 0.8313
0.4463 23.68 900 0.8580 0.8918 0.9051 0.8984 0.8313
0.0611 26.32 1000 0.8428 0.8993 0.9046 0.9019 0.8354

Framework versions

  • Transformers 4.36.0
  • Pytorch 2.0.0
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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