layoutlmv3-finetuned-invoice

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

  • Loss: 0.0012
  • Precision: 1.0
  • Recall: 1.0
  • F1: 1.0
  • Accuracy: 1.0

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: 2000

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 2.0 100 0.0877 0.94 0.9533 0.9466 0.9937
No log 4.0 200 0.0244 0.972 0.9858 0.9789 0.9971
No log 6.0 300 0.0162 0.972 0.9858 0.9789 0.9971
No log 8.0 400 0.0142 0.972 0.9858 0.9789 0.9971
0.1178 10.0 500 0.0119 0.972 0.9858 0.9789 0.9971
0.1178 12.0 600 0.0122 0.972 0.9858 0.9789 0.9971
0.1178 14.0 700 0.0035 1.0 0.9980 0.9990 0.9998
0.1178 16.0 800 0.0023 1.0 1.0 1.0 1.0
0.1178 18.0 900 0.0029 0.9960 0.9980 0.9970 0.9996
0.0064 20.0 1000 0.0027 0.9960 0.9980 0.9970 0.9996
0.0064 22.0 1100 0.0020 0.9980 1.0 0.9990 0.9998
0.0064 24.0 1200 0.0022 0.9980 1.0 0.9990 0.9998
0.0064 26.0 1300 0.0013 1.0 1.0 1.0 1.0
0.0064 28.0 1400 0.0014 0.9980 1.0 0.9990 0.9998
0.0025 30.0 1500 0.0012 1.0 1.0 1.0 1.0
0.0025 32.0 1600 0.0011 1.0 1.0 1.0 1.0
0.0025 34.0 1700 0.0011 1.0 1.0 1.0 1.0
0.0025 36.0 1800 0.0010 1.0 1.0 1.0 1.0
0.0025 38.0 1900 0.0010 1.0 1.0 1.0 1.0
0.0019 40.0 2000 0.0010 1.0 1.0 1.0 1.0

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Evaluation results