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layoutlmv3-finetuned-funsd

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

  • Loss: 1.1164
  • Precision: 0.9026
  • Recall: 0.913
  • F1: 0.9078
  • Accuracy: 0.8330

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: 1e-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 10.0 100 0.5238 0.8366 0.886 0.8606 0.8410
No log 20.0 200 0.6930 0.8751 0.8965 0.8857 0.8322
No log 30.0 300 0.7784 0.8902 0.908 0.8990 0.8414
No log 40.0 400 0.9056 0.8916 0.905 0.8983 0.8364
0.2429 50.0 500 1.0016 0.8954 0.9075 0.9014 0.8298
0.2429 60.0 600 1.0097 0.8899 0.897 0.8934 0.8294
0.2429 70.0 700 1.0722 0.9035 0.9085 0.9060 0.8315
0.2429 80.0 800 1.0884 0.8905 0.9105 0.9004 0.8269
0.2429 90.0 900 1.1292 0.8938 0.909 0.9013 0.8279
0.0098 100.0 1000 1.1164 0.9026 0.913 0.9078 0.8330

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