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layoutlm_model
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: 1.6891
- Answer: {'precision': 0.020451339915373765, 'recall': 0.03584672435105068, 'f1': 0.026044005388414906, 'number': 809}
- Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}
- Question: {'precision': 0.12158341187558906, 'recall': 0.12112676056338029, 'f1': 0.1213546566321731, 'number': 1065}
- Overall Precision: 0.0637
- Overall Recall: 0.0793
- Overall F1: 0.0707
- Overall Accuracy: 0.3724
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: 16
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|
| 1.8693 | 1.0 | 10 | 1.6891 | {'precision': 0.020451339915373765, 'recall': 0.03584672435105068, 'f1': 0.026044005388414906, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.12158341187558906, 'recall': 0.12112676056338029, 'f1': 0.1213546566321731, 'number': 1065} | 0.0637 | 0.0793 | 0.0707 | 0.3724 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
