---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-phising-classifier-teacher
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-phising-classifier-teacher

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3006
- Accuracy: 0.87
- Auc: 0.953

## 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_BNB 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   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 0.4732        | 1.0   | 350  | 0.3613          | 0.83     | 0.921 |
| 0.3752        | 2.0   | 700  | 0.3591          | 0.853    | 0.938 |
| 0.338         | 3.0   | 1050 | 0.3097          | 0.862    | 0.944 |
| 0.3368        | 4.0   | 1400 | 0.2967          | 0.867    | 0.947 |
| 0.3458        | 5.0   | 1750 | 0.3043          | 0.877    | 0.949 |
| 0.3303        | 6.0   | 2100 | 0.3197          | 0.855    | 0.95  |
| 0.3172        | 7.0   | 2450 | 0.3629          | 0.852    | 0.952 |
| 0.3147        | 8.0   | 2800 | 0.2844          | 0.872    | 0.952 |
| 0.3063        | 9.0   | 3150 | 0.2864          | 0.883    | 0.953 |
| 0.3145        | 10.0  | 3500 | 0.3006          | 0.87     | 0.953 |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1