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layoutlmv3-fine-tuned-funsd-kie

Token Classification
Transformers
Safetensors
layoutlmv3
Generated from Trainer
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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: test
    results: []

Visualize in Weights & Biases

test

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: 0.8476
  • Precision: 0.8955
  • Recall: 0.9071
  • F1: 0.9013
  • Accuracy: 0.8691

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
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 75 0.9234 0.6139 0.7526 0.6762 0.7416
No log 2.0 150 0.6101 0.7549 0.8341 0.7925 0.7940
No log 3.0 225 0.5135 0.8332 0.8882 0.8598 0.8091
No log 4.0 300 0.5467 0.8189 0.8624 0.8401 0.8109
No log 5.0 375 0.4879 0.8660 0.9051 0.8851 0.8504
No log 6.0 450 0.5352 0.8787 0.9180 0.8980 0.8480
0.5752 7.0 525 0.5900 0.8730 0.8982 0.8854 0.8343
0.5752 8.0 600 0.6014 0.8832 0.9016 0.8923 0.8506
0.5752 9.0 675 0.6173 0.8883 0.9126 0.9003 0.8538
0.5752 10.0 750 0.6278 0.8787 0.9141 0.8960 0.8571
0.5752 11.0 825 0.6573 0.8612 0.9155 0.8876 0.8326
0.5752 12.0 900 0.7333 0.8818 0.9006 0.8911 0.8387
0.5752 13.0 975 0.7489 0.8888 0.9136 0.9010 0.8502
0.1263 14.0 1050 0.7719 0.8908 0.8997 0.8952 0.8318
0.1263 15.0 1125 0.8295 0.8945 0.9101 0.9022 0.8438
0.1263 16.0 1200 0.8447 0.8798 0.9126 0.8959 0.8465
0.1263 17.0 1275 0.8359 0.9090 0.8932 0.9010 0.8486
0.1263 18.0 1350 0.8430 0.8966 0.9091 0.9028 0.8414
0.1263 19.0 1425 0.8179 0.8854 0.9021 0.8937 0.8400
0.0482 20.0 1500 0.8950 0.8968 0.8982 0.8975 0.8475
0.0482 21.0 1575 0.8790 0.9053 0.9121 0.9087 0.8565
0.0482 22.0 1650 0.7915 0.9056 0.9101 0.9078 0.8595
0.0482 23.0 1725 0.8760 0.8938 0.8952 0.8945 0.8504
0.0482 24.0 1800 0.8320 0.9113 0.9086 0.9100 0.8625
0.0482 25.0 1875 0.8880 0.9017 0.9021 0.9019 0.8538
0.0482 26.0 1950 0.8611 0.9083 0.9101 0.9092 0.8499
0.0163 27.0 2025 0.8747 0.9068 0.9086 0.9077 0.8600
0.0163 28.0 2100 0.8476 0.8955 0.9071 0.9013 0.8691

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1