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Language-levels-LayoutLMv3-v5

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layoutlmv3
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Language-levels-LayoutLMv3-v5 / README.md
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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-language-levels-v5-4000
    results: []

layoutlmv3-finetuned-language-levels-v5-4000

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: 0.0913
  • Precision: 1.0
  • Recall: 1.0
  • F1: 1.0
  • Accuracy: 0.9824

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: 4000

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 0.2618 100 0.8184 0.9647 0.9630 0.9639 0.6971
No log 0.5236 200 0.6254 0.9743 0.9815 0.9779 0.7404
No log 0.7853 300 0.4760 0.9926 0.9944 0.9935 0.7981
No log 1.0471 400 0.3675 0.9798 0.9889 0.9843 0.8910
0.6763 1.3089 500 0.0913 1.0 1.0 1.0 0.9824
0.6763 1.5707 600 0.0375 1.0 1.0 1.0 0.9904
0.6763 1.8325 700 0.0149 1.0 1.0 1.0 1.0
0.6763 2.0942 800 0.0078 1.0 1.0 1.0 1.0
0.6763 2.3560 900 0.0047 1.0 1.0 1.0 1.0
0.037 2.6178 1000 0.0037 1.0 1.0 1.0 1.0
0.037 2.8796 1100 0.0030 1.0 1.0 1.0 1.0
0.037 3.1414 1200 0.0026 1.0 1.0 1.0 1.0
0.037 3.4031 1300 0.0022 1.0 1.0 1.0 1.0
0.037 3.6649 1400 0.0019 1.0 1.0 1.0 1.0
0.0046 3.9267 1500 0.0017 1.0 1.0 1.0 1.0
0.0046 4.1885 1600 0.0016 1.0 1.0 1.0 1.0
0.0046 4.4503 1700 0.0014 1.0 1.0 1.0 1.0
0.0046 4.7120 1800 0.0013 1.0 1.0 1.0 1.0
0.0046 4.9738 1900 0.0012 1.0 1.0 1.0 1.0
0.0025 5.2356 2000 0.0011 1.0 1.0 1.0 1.0
0.0025 5.4974 2100 0.0010 1.0 1.0 1.0 1.0
0.0025 5.7592 2200 0.0010 1.0 1.0 1.0 1.0
0.0025 6.0209 2300 0.0009 1.0 1.0 1.0 1.0
0.0025 6.2827 2400 0.0009 1.0 1.0 1.0 1.0
0.0017 6.5445 2500 0.0008 1.0 1.0 1.0 1.0
0.0017 6.8063 2600 0.0008 1.0 1.0 1.0 1.0
0.0017 7.0681 2700 0.0007 1.0 1.0 1.0 1.0
0.0017 7.3298 2800 0.0007 1.0 1.0 1.0 1.0
0.0017 7.5916 2900 0.0007 1.0 1.0 1.0 1.0
0.0013 7.8534 3000 0.0007 1.0 1.0 1.0 1.0
0.0013 8.1152 3100 0.0006 1.0 1.0 1.0 1.0
0.0013 8.3770 3200 0.0006 1.0 1.0 1.0 1.0
0.0013 8.6387 3300 0.0006 1.0 1.0 1.0 1.0
0.0013 8.9005 3400 0.0006 1.0 1.0 1.0 1.0
0.0011 9.1623 3500 0.0006 1.0 1.0 1.0 1.0
0.0011 9.4241 3600 0.0006 1.0 1.0 1.0 1.0
0.0011 9.6859 3700 0.0006 1.0 1.0 1.0 1.0
0.0011 9.9476 3800 0.0005 1.0 1.0 1.0 1.0
0.0011 10.2094 3900 0.0005 1.0 1.0 1.0 1.0
0.001 10.4712 4000 0.0005 1.0 1.0 1.0 1.0

Framework versions

  • Transformers 4.43.3
  • Pytorch 2.1.0+cu118
  • Datasets 2.20.0
  • Tokenizers 0.19.1