---
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
  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

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: 0.2994
- Accuracy: 0.871
- Auc: 0.951

## 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_FUSED 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   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 0.4954        | 1.0   | 263  | 0.4188          | 0.791    | 0.913 |
| 0.3914        | 2.0   | 526  | 0.3616          | 0.818    | 0.931 |
| 0.3813        | 3.0   | 789  | 0.3164          | 0.86     | 0.938 |
| 0.3589        | 4.0   | 1052 | 0.4471          | 0.811    | 0.942 |
| 0.3513        | 5.0   | 1315 | 0.3300          | 0.862    | 0.946 |
| 0.3547        | 6.0   | 1578 | 0.3082          | 0.867    | 0.948 |
| 0.3224        | 7.0   | 1841 | 0.2914          | 0.864    | 0.949 |
| 0.3301        | 8.0   | 2104 | 0.2986          | 0.876    | 0.949 |
| 0.3165        | 9.0   | 2367 | 0.2901          | 0.862    | 0.95  |
| 0.3061        | 10.0  | 2630 | 0.2994          | 0.871    | 0.951 |


### Framework versions

- Transformers 5.9.0
- Pytorch 2.11.0
- Datasets 4.8.5
- Tokenizers 0.22.2