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test

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

  • Loss: 0.0899
  • Precision: 0.9736
  • Recall: 0.9752
  • F1: 0.9744
  • Accuracy: 0.9924

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 0.5291 100 0.4956 0.7821 0.7724 0.7772 0.9413
No log 1.0582 200 0.1802 0.9285 0.9247 0.9266 0.9761
No log 1.5873 300 0.1465 0.9334 0.9512 0.9422 0.9841
No log 2.1164 400 0.1309 0.9447 0.9611 0.9528 0.9876
0.3392 2.6455 500 0.1095 0.9516 0.9594 0.9555 0.9891
0.3392 3.1746 600 0.1022 0.9573 0.9652 0.9613 0.9915
0.3392 3.7037 700 0.1081 0.9573 0.9661 0.9617 0.9918
0.3392 4.2328 800 0.0922 0.9726 0.9694 0.9710 0.9920
0.3392 4.7619 900 0.0930 0.9702 0.9702 0.9702 0.9916
0.0282 5.2910 1000 0.0899 0.9736 0.9752 0.9744 0.9924

Framework versions

  • Transformers 4.47.0.dev0
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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