---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: phishing_detection_fine_tuned_bert
  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. -->

# phishing_detection_fine_tuned_bert

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3343
- Accuracy: 0.8565
- F1: 0.8573
- Precision: 0.8596
- Recall: 0.8565

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.411         | 1.0   | 3622  | 0.3300          | 0.8222   | 0.8242 | 0.8509    | 0.8222 |
| 0.4471        | 2.0   | 7244  | 0.6779          | 0.8154   | 0.8067 | 0.8274    | 0.8154 |
| 0.6583        | 3.0   | 10866 | 0.6717          | 0.6079   | 0.4597 | 0.3695    | 0.6079 |
| 0.6286        | 4.0   | 14488 | 0.6698          | 0.6079   | 0.4597 | 0.3695    | 0.6079 |
| 0.6527        | 5.0   | 18110 | 0.6697          | 0.6079   | 0.4597 | 0.3695    | 0.6079 |
| 0.336         | 6.0   | 21732 | 0.4681          | 0.7707   | 0.7719 | 0.8293    | 0.7707 |
| 0.5686        | 7.0   | 25354 | 0.6242          | 0.5740   | 0.5518 | 0.7128    | 0.5740 |
| 0.334         | 8.0   | 28976 | 0.3666          | 0.8279   | 0.8298 | 0.8433    | 0.8279 |
| 0.4017        | 9.0   | 32598 | 0.3711          | 0.8571   | 0.8561 | 0.8564    | 0.8571 |
| 0.2285        | 10.0  | 36220 | 0.3343          | 0.8565   | 0.8573 | 0.8596    | 0.8565 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0