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metadata
tags:
  - generated_from_keras_callback
model-index:
  - name: layoutlm-funsd-sequence-tf
    results: []

layoutlm-funsd-sequence-tf

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

  • Train Loss: 0.2348
  • Validation Loss: 0.6737
  • Train Overall Precision: 0.7356
  • Train Overall Recall: 0.7998
  • Train Overall F1: 0.7663
  • Train Overall Accuracy: 0.8220
  • Epoch: 7

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:

  • optimizer: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
  • training_precision: mixed_float16

Training results

Train Loss Validation Loss Train Overall Precision Train Overall Recall Train Overall F1 Train Overall Accuracy Epoch
1.7150 1.4139 0.2373 0.2860 0.2594 0.4954 0
1.1803 0.9205 0.5676 0.6322 0.5981 0.7008 1
0.7884 0.7100 0.6202 0.7250 0.6685 0.7735 2
0.5877 0.6476 0.6689 0.7662 0.7142 0.7942 3
0.4490 0.6179 0.7133 0.8078 0.7576 0.8066 4
0.3746 0.6305 0.7176 0.7878 0.7510 0.8129 5
0.3082 0.6924 0.7163 0.8018 0.7566 0.7937 6
0.2348 0.6737 0.7356 0.7998 0.7663 0.8220 7

Framework versions

  • Transformers 4.28.1
  • TensorFlow 2.12.0
  • Datasets 2.11.0
  • Tokenizers 0.13.3