metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- text-classification
- generated_from_trainer
datasets:
- zefang-liu/phishing-email-dataset
metrics:
- accuracy
model-index:
- name: results
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: zefang-liu/phishing-email-dataset
type: zefang-liu/phishing-email-dataset
metrics:
- name: Accuracy
type: accuracy
value: 0.9774617654950363
results
This model is a fine-tuned version of bert-base-uncased on the zefang-liu/phishing-email-dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.0992
- Accuracy: 0.9775
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0634 | 1.0 | 1863 | 0.0950 | 0.9713 |
| 0.0336 | 2.0 | 3726 | 0.0842 | 0.9785 |
| 0.0269 | 3.0 | 5589 | 0.0835 | 0.9785 |
| 0.0452 | 4.0 | 7452 | 0.1083 | 0.9777 |
| 0.0233 | 5.0 | 9315 | 0.0992 | 0.9775 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1