test

This model is a fine-tuned version of microsoft/layoutlmv3-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2843
  • Precision: 0.4118
  • Recall: 0.8235
  • F1: 0.5490
  • Accuracy: 0.9485

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 8.33 100 0.6271 0.1864 0.6471 0.2895 0.8757
No log 16.67 200 0.1736 0.52 0.7647 0.6190 0.9734
No log 25.0 300 0.1302 0.5714 0.9412 0.7111 0.9734
No log 33.33 400 0.2835 0.5333 0.9412 0.6809 0.9556
0.287 41.67 500 0.0924 0.4828 0.8235 0.6087 0.9805
0.287 50.0 600 0.2594 0.4412 0.8824 0.5882 0.9485
0.287 58.33 700 0.3172 0.4412 0.8824 0.5882 0.9467
0.287 66.67 800 0.2447 0.4545 0.8824 0.6 0.9520
0.287 75.0 900 0.2941 0.4118 0.8235 0.5490 0.9485
0.013 83.33 1000 0.2843 0.4118 0.8235 0.5490 0.9485

Framework versions

  • Transformers 4.34.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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