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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: 0.0048
  • 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 0.0785 0.9 0.9128 0.9063 0.9895
No log 4.0 200 0.0226 0.972 0.9858 0.9789 0.9971
No log 6.0 300 0.0167 0.972 0.9858 0.9789 0.9971
No log 8.0 400 0.0119 0.972 0.9858 0.9789 0.9971
0.1245 10.0 500 0.0048 1.0 1.0 1.0 1.0
0.1245 12.0 600 0.0034 1.0 1.0 1.0 1.0
0.1245 14.0 700 0.0026 1.0 1.0 1.0 1.0
0.1245 16.0 800 0.0022 1.0 1.0 1.0 1.0
0.1245 18.0 900 0.0019 1.0 1.0 1.0 1.0
0.0051 20.0 1000 0.0017 1.0 1.0 1.0 1.0
0.0051 22.0 1100 0.0015 1.0 1.0 1.0 1.0
0.0051 24.0 1200 0.0014 1.0 1.0 1.0 1.0
0.0051 26.0 1300 0.0013 1.0 1.0 1.0 1.0
0.0051 28.0 1400 0.0012 1.0 1.0 1.0 1.0
0.0026 30.0 1500 0.0011 1.0 1.0 1.0 1.0
0.0026 32.0 1600 0.0011 1.0 1.0 1.0 1.0
0.0026 34.0 1700 0.0010 1.0 1.0 1.0 1.0
0.0026 36.0 1800 0.0010 1.0 1.0 1.0 1.0
0.0026 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 4.27.0.dev0
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2
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Evaluation results