bert-base-cased
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4145
- Precision: 0.4029
- Recall: 0.2740
- F1: 0.3262
- Accuracy: 0.9602
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: 2e-05
- 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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|
| 0.0002 | 1.0 | 7365 | 0.3903 | 0.4151 | 0.2241 | 0.2911 | 0.9574 |
| 0.0003 | 2.0 | 14730 | 0.4288 | 0.3681 | 0.2006 | 0.2597 | 0.9580 |
| 0.0 | 3.0 | 22095 | 0.4145 | 0.4029 | 0.2740 | 0.3262 | 0.9602 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
