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layoutlmv3-finetuned-cord

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

  • Loss: 0.1845
  • Precision: 0.9620
  • Recall: 0.9656
  • F1: 0.9638
  • Accuracy: 0.9682

The script for training can be found here: https://github.com/huggingface/transformers/tree/main/examples/research_projects/layoutlmv3

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • 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 2.0 100 0.5257 0.8223 0.8555 0.8386 0.8710
No log 4.0 200 0.3200 0.9118 0.9281 0.9199 0.9317
No log 6.0 300 0.2449 0.9298 0.9424 0.9361 0.9465
No log 8.0 400 0.1923 0.9472 0.9536 0.9504 0.9597
0.4328 10.0 500 0.1857 0.9591 0.9656 0.9623 0.9682
0.4328 12.0 600 0.2073 0.9597 0.9618 0.9607 0.9656
0.4328 14.0 700 0.1804 0.9634 0.9663 0.9649 0.9703
0.4328 16.0 800 0.1882 0.9634 0.9648 0.9641 0.9665
0.4328 18.0 900 0.1800 0.9619 0.9648 0.9634 0.9677
0.0318 20.0 1000 0.1845 0.9620 0.9656 0.9638 0.9682

Framework versions

  • Transformers 4.19.0.dev0
  • Pytorch 1.11.0+cu113
  • Datasets 2.0.0
  • Tokenizers 0.11.6
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Evaluation results