nexon_jan_2023

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

  • Loss: 0.0380
  • Precision: 0.9756
  • Recall: 0.9302
  • F1: 0.9524
  • Accuracy: 0.9971

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: 1500

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 16.67 100 0.1998 0.6286 0.5116 0.5641 0.9571
No log 33.33 200 0.0616 0.9756 0.9302 0.9524 0.9971
No log 50.0 300 0.0439 0.9756 0.9302 0.9524 0.9971
No log 66.67 400 0.0404 0.9756 0.9302 0.9524 0.9971
0.1151 83.33 500 0.0389 0.9756 0.9302 0.9524 0.9971
0.1151 100.0 600 0.0380 0.9756 0.9302 0.9524 0.9971
0.1151 116.67 700 0.0378 0.9756 0.9302 0.9524 0.9971
0.1151 133.33 800 0.0379 0.9756 0.9302 0.9524 0.9971
0.1151 150.0 900 0.0378 0.9756 0.9302 0.9524 0.9971
0.009 166.67 1000 0.0378 0.9756 0.9302 0.9524 0.9971
0.009 183.33 1100 0.0378 0.9756 0.9302 0.9524 0.9971
0.009 200.0 1200 0.0379 0.9756 0.9302 0.9524 0.9971
0.009 216.67 1300 0.0379 0.9756 0.9302 0.9524 0.9971
0.009 233.33 1400 0.0379 0.9756 0.9302 0.9524 0.9971
0.0064 250.0 1500 0.0380 0.9756 0.9302 0.9524 0.9971

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1+cu116
  • Datasets 2.2.2
  • Tokenizers 0.13.2
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Evaluation results