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model-v2-2024-04-22

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

  • Loss: 0.7650
  • Precision: 0.7666
  • Recall: 0.7514
  • F1: 0.7589
  • Accuracy: 0.8762

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 2.22 100 1.2087 0.5724 0.2458 0.3439 0.7248
No log 4.44 200 0.7936 0.6667 0.5650 0.6116 0.82
No log 6.67 300 0.6730 0.7273 0.6780 0.7018 0.8543
No log 8.89 400 0.6465 0.7618 0.7316 0.7464 0.8724
0.7871 11.11 500 0.6474 0.7388 0.7429 0.7408 0.8657
0.7871 13.33 600 0.7060 0.7514 0.7429 0.7472 0.8724
0.7871 15.56 700 0.7356 0.7507 0.7401 0.7454 0.8705
0.7871 17.78 800 0.7483 0.7522 0.7373 0.7447 0.8695
0.7871 20.0 900 0.7577 0.7572 0.7401 0.7486 0.8724
0.1672 22.22 1000 0.7650 0.7666 0.7514 0.7589 0.8762

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.13.3
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