ft-bert-base-uncased-for-binary-search
This model is a fine-tuned version of bert-base-uncased on the https://www.kaggle.com/datasets/skywardai/network-vulnerability dataset. It achieves the following results on the evaluation set:
- Loss: 0.1812
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1845 | 1.0 | 63 | 0.1808 |
| 0.1793 | 2.0 | 126 | 0.1811 |
| 0.2158 | 3.0 | 189 | 0.1812 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.2.2
- Datasets 3.1.0
- Tokenizers 0.20.1