layoutlm-funsd / README.md
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End of training
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metadata
base_model: microsoft/layoutlm-base-uncased
tags:
  - generated_from_trainer
datasets:
  - funsd
model-index:
  - name: layoutlm-funsd
    results: []

layoutlm-funsd

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

  • Loss: 1.0643
  • Answer: {'precision': 0.384928716904277, 'recall': 0.4672435105067985, 'f1': 0.4221105527638191, 'number': 809}
  • Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}
  • Question: {'precision': 0.5277088502894954, 'recall': 0.5990610328638498, 'f1': 0.5611257695690414, 'number': 1065}
  • Overall Precision: 0.4583
  • Overall Recall: 0.5098
  • Overall F1: 0.4827
  • Overall Accuracy: 0.6395

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: 3e-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: 1

Training results

Training Loss Epoch Step Validation Loss Answer Header Question Overall Precision Overall Recall Overall F1 Overall Accuracy
1.4286 1.0 75 1.0643 {'precision': 0.384928716904277, 'recall': 0.4672435105067985, 'f1': 0.4221105527638191, 'number': 809} {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} {'precision': 0.5277088502894954, 'recall': 0.5990610328638498, 'f1': 0.5611257695690414, 'number': 1065} 0.4583 0.5098 0.4827 0.6395

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1