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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: 1.5315
- Answer: {'precision': 0.03470437017994859, 'recall': 0.03337453646477132, 'f1': 0.03402646502835539, 'number': 809}
- Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}
- Question: {'precision': 0.3425827107790822, 'recall': 0.30140845070422534, 'f1': 0.32067932067932065, 'number': 1065}
- Overall Precision: 0.2029
- Overall Recall: 0.1746
- Overall F1: 0.1877
- Overall Accuracy: 0.3869
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Answer | Header | Question | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|---|
| 1.7866 | 1.0 | 10 | 1.6364 | {'precision': 0.014164305949008499, 'recall': 0.012360939431396786, 'f1': 0.0132013201320132, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.20684931506849316, 'recall': 0.14178403755868543, 'f1': 0.16824512534818942, 'number': 1065} | 0.1121 | 0.0808 | 0.0939 | 0.3375 |
| 1.5665 | 2.0 | 20 | 1.5315 | {'precision': 0.03470437017994859, 'recall': 0.03337453646477132, 'f1': 0.03402646502835539, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.3425827107790822, 'recall': 0.30140845070422534, 'f1': 0.32067932067932065, 'number': 1065} | 0.2029 | 0.1746 | 0.1877 | 0.3869 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
