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lilt-en-funsd
This model is a fine-tuned version of SCUT-DLVCLab/lilt-roberta-en-base on the mydata dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- In: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6}
- Ear: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6}
- Overall Precision: 1.0
- Overall Recall: 1.0
- Overall F1: 1.0
- Overall Accuracy: 1.0
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: 5e-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
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | In | Ear | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|
| 0.017 | 66.67 | 200 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 133.33 | 400 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 200.0 | 600 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 266.67 | 800 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 333.33 | 1000 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 400.0 | 1200 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 466.67 | 1400 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 533.33 | 1600 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 600.0 | 1800 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 666.67 | 2000 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 733.33 | 2200 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 800.0 | 2400 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6} | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 1.8.0+cu101
- Datasets 2.12.0
- Tokenizers 0.13.3
