---
base_model: google-bert/bert-base-uncased
library_name: transformers
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert-phishing-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-phishing-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: 0.3027
- Accuracy: 0.869
- Auc: 0.95

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 0.4989        | 1.0   | 263  | 0.3952          | 0.798    | 0.913 |
| 0.3791        | 2.0   | 526  | 0.3593          | 0.824    | 0.932 |
| 0.3689        | 3.0   | 789  | 0.3076          | 0.867    | 0.942 |
| 0.3466        | 4.0   | 1052 | 0.3502          | 0.849    | 0.944 |
| 0.3506        | 5.0   | 1315 | 0.3051          | 0.858    | 0.946 |
| 0.3298        | 6.0   | 1578 | 0.3215          | 0.858    | 0.948 |
| 0.3224        | 7.0   | 1841 | 0.2880          | 0.862    | 0.95  |
| 0.3082        | 8.0   | 2104 | 0.2869          | 0.871    | 0.95  |
| 0.34          | 9.0   | 2367 | 0.2890          | 0.862    | 0.95  |
| 0.3099        | 10.0  | 2630 | 0.3027          | 0.869    | 0.95  |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.0