metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: phishing_detection_fine_tuned_bert
results: []
phishing_detection_fine_tuned_bert
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3343
- Accuracy: 0.8565
- F1: 0.8573
- Precision: 0.8596
- Recall: 0.8565
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: 8
- eval_batch_size: 8
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.411 | 1.0 | 3622 | 0.3300 | 0.8222 | 0.8242 | 0.8509 | 0.8222 |
| 0.4471 | 2.0 | 7244 | 0.6779 | 0.8154 | 0.8067 | 0.8274 | 0.8154 |
| 0.6583 | 3.0 | 10866 | 0.6717 | 0.6079 | 0.4597 | 0.3695 | 0.6079 |
| 0.6286 | 4.0 | 14488 | 0.6698 | 0.6079 | 0.4597 | 0.3695 | 0.6079 |
| 0.6527 | 5.0 | 18110 | 0.6697 | 0.6079 | 0.4597 | 0.3695 | 0.6079 |
| 0.336 | 6.0 | 21732 | 0.4681 | 0.7707 | 0.7719 | 0.8293 | 0.7707 |
| 0.5686 | 7.0 | 25354 | 0.6242 | 0.5740 | 0.5518 | 0.7128 | 0.5740 |
| 0.334 | 8.0 | 28976 | 0.3666 | 0.8279 | 0.8298 | 0.8433 | 0.8279 |
| 0.4017 | 9.0 | 32598 | 0.3711 | 0.8571 | 0.8561 | 0.8564 | 0.8571 |
| 0.2285 | 10.0 | 36220 | 0.3343 | 0.8565 | 0.8573 | 0.8596 | 0.8565 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0