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layoutlmv3-finetuned-cord_100
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metadata
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: layoutlmv3-finetuned-cord_100
    results: []

layoutlmv3-finetuned-cord_100

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

  • Loss: 0.1687
  • Precision: 0.9382
  • Recall: 0.9574
  • F1: 0.9477
  • Accuracy: 0.9597

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: 5
  • eval_batch_size: 5
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 2500

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.56 250 0.3730 0.8662 0.8708 0.8685 0.9042
0.3943 3.12 500 0.2683 0.8939 0.9027 0.8983 0.9279
0.3943 4.69 750 0.2232 0.9248 0.9339 0.9293 0.9474
0.1559 6.25 1000 0.2129 0.9301 0.9407 0.9354 0.9504
0.1559 7.81 1250 0.1782 0.9289 0.9529 0.9407 0.9563
0.082 9.38 1500 0.1876 0.9327 0.9483 0.9405 0.9555
0.082 10.94 1750 0.1746 0.9416 0.9559 0.9487 0.9606
0.0486 12.5 2000 0.1848 0.9349 0.9498 0.9423 0.9550
0.0486 14.06 2250 0.1739 0.9439 0.9590 0.9514 0.9623
0.0351 15.62 2500 0.1687 0.9382 0.9574 0.9477 0.9597

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2