<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
testing_img_token
This model is a fine-tuned version of SCUT-DLVCLab/lilt-roberta-en-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9187
- Eading: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
- Ext: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}
- Ub heading: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15}
- Overall Precision: 0.0
- Overall Recall: 0.0
- Overall F1: 0.0
- Overall Accuracy: 0.4848
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Eading | Ext | Ub heading | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|---|
| 1.4635 | 1.43 | 10 | 1.2178 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0 | 0.0 | 0.0 | 0.4848 |
| 1.2206 | 2.86 | 20 | 1.0016 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0 | 0.0 | 0.0 | 0.4848 |
| 1.0569 | 4.29 | 30 | 0.9783 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0 | 0.0 | 0.0 | 0.4848 |
| 1.0201 | 5.71 | 40 | 0.9273 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0 | 0.0 | 0.0 | 0.4848 |
| 0.9888 | 7.14 | 50 | 0.9187 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0 | 0.0 | 0.0 | 0.4848 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2
