lilt-en-funsd-custom
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: 0.0023
- In: {'precision': 0.5, 'recall': 0.5, 'f1': 0.5, 'number': 2}
- Ear: {'precision': 0.6666666666666666, 'recall': 1.0, 'f1': 0.8, 'number': 2}
- Overall Precision: 0.6
- Overall Recall: 0.75
- Overall F1: 0.6667
- Overall Accuracy: 0.9984
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: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | In | Ear | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|
| 0.1628 | 25.0 | 50 | 0.0023 | {'precision': 0.5, 'recall': 0.5, 'f1': 0.5, 'number': 2} | {'precision': 0.6666666666666666, 'recall': 1.0, 'f1': 0.8, 'number': 2} | 0.6 | 0.75 | 0.6667 | 0.9984 |
| 0.0002 | 50.0 | 100 | 0.0015 | {'precision': 0.5, 'recall': 0.5, 'f1': 0.5, 'number': 2} | {'precision': 0.6666666666666666, 'recall': 1.0, 'f1': 0.8, 'number': 2} | 0.6 | 0.75 | 0.6667 | 0.9984 |
| 0.0001 | 75.0 | 150 | 0.0020 | {'precision': 0.5, 'recall': 0.5, 'f1': 0.5, 'number': 2} | {'precision': 0.6666666666666666, 'recall': 1.0, 'f1': 0.8, 'number': 2} | 0.6 | 0.75 | 0.6667 | 0.9984 |
| 0.0 | 100.0 | 200 | 0.0020 | {'precision': 0.5, 'recall': 0.5, 'f1': 0.5, 'number': 2} | {'precision': 0.6666666666666666, 'recall': 1.0, 'f1': 0.8, 'number': 2} | 0.6 | 0.75 | 0.6667 | 0.9984 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 1.8.0+cu101
- Datasets 2.12.0
- Tokenizers 0.13.3