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metadata
license: cc-by-nc-sa-4.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: layoutlmv3-finetuned-funsd2
    results: []

layoutlmv3-finetuned-funsd2

This model is a fine-tuned version of microsoft/layoutlmv3-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8330
  • Precision: 0.9046
  • Recall: 0.9105
  • F1: 0.9076
  • Accuracy: 0.8536

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: 4
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.32 50 0.6163 0.8088 0.8965 0.8504 0.8088
No log 2.63 100 0.5416 0.8037 0.868 0.8346 0.8134
No log 3.95 150 0.5572 0.8446 0.8885 0.8660 0.8385
No log 5.26 200 0.7317 0.8458 0.8555 0.8506 0.8124
No log 6.58 250 0.7220 0.8877 0.8935 0.8906 0.8385
No log 7.89 300 0.8070 0.8778 0.9055 0.8915 0.8436
No log 9.21 350 0.7895 0.8969 0.913 0.9049 0.8477
No log 10.53 400 0.8168 0.8935 0.889 0.8912 0.8412
No log 11.84 450 0.8233 0.8955 0.917 0.9061 0.8521
0.2564 13.16 500 0.8330 0.9046 0.9105 0.9076 0.8536

Framework versions

  • Transformers 4.12.5
  • Pytorch 1.10.0+cu111
  • Datasets 2.13.2
  • Tokenizers 0.10.1