metadata
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: phishing_2_1
results: []
phishing_2_1
This model is a fine-tuned version of bert-large-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3498
- Accuracy: 0.9634
- Precision: 0.9918
- Recall: 0.9345
- False Positive Rate: 0.0077
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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | False Positive Rate |
|---|---|---|---|---|---|---|---|
| 0.365 | 1.0 | 3025 | 0.3632 | 0.9480 | 0.9861 | 0.9088 | 0.0128 |
| 0.3453 | 2.0 | 6050 | 0.3405 | 0.9727 | 0.9752 | 0.9700 | 0.0247 |
| 0.3623 | 3.0 | 9075 | 0.3596 | 0.9536 | 0.9861 | 0.9202 | 0.0130 |
| 0.3498 | 4.0 | 12100 | 0.3498 | 0.9634 | 0.9918 | 0.9345 | 0.0077 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2