metadata
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-phishing-classifier_teacher
results: []
bert-phishing-classifier_teacher
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2941
- Accuracy: 0.873
- Auc: 0.952
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc |
|---|---|---|---|---|---|
| 0.4992 | 1.0 | 263 | 0.3864 | 0.807 | 0.914 |
| 0.4029 | 2.0 | 526 | 0.3635 | 0.838 | 0.934 |
| 0.3699 | 3.0 | 789 | 0.4964 | 0.78 | 0.942 |
| 0.3364 | 4.0 | 1052 | 0.3216 | 0.858 | 0.938 |
| 0.3626 | 5.0 | 1315 | 0.3473 | 0.858 | 0.948 |
| 0.3189 | 6.0 | 1578 | 0.2932 | 0.88 | 0.95 |
| 0.3217 | 7.0 | 1841 | 0.2930 | 0.876 | 0.949 |
| 0.3355 | 8.0 | 2104 | 0.3004 | 0.864 | 0.95 |
| 0.3103 | 9.0 | 2367 | 0.2891 | 0.867 | 0.951 |
| 0.2987 | 10.0 | 2630 | 0.2941 | 0.873 | 0.952 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0