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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: 0.2763
  • Precision: 0.5109
  • Recall: 0.6026
  • F1: 0.5529
  • Accuracy: 0.9222

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 0.6800 0.3371 0.3846 0.3593 0.7682
No log 16.67 200 0.3088 0.5204 0.6538 0.5795 0.9156
No log 25.0 300 0.2142 0.5326 0.6282 0.5765 0.9305
No log 33.33 400 0.2301 0.5795 0.6538 0.6145 0.9288
0.4115 41.67 500 0.2426 0.5618 0.6410 0.5988 0.9272
0.4115 50.0 600 0.4171 0.6190 0.6667 0.6420 0.8924
0.4115 58.33 700 0.2265 0.5393 0.6154 0.5749 0.9371
0.4115 66.67 800 0.2869 0.5506 0.6282 0.5868 0.9156
0.4115 75.0 900 0.2633 0.5568 0.6282 0.5904 0.9272
0.0231 83.33 1000 0.2763 0.5109 0.6026 0.5529 0.9222

Framework versions

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