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

# distilbert-zim-phishing

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3919
- Accuracy: 0.9032
- Precision: 0.8667
- Recall: 0.9286
- F1: 0.8966

## 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: 2e-05
- train_batch_size: 4
- 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
- lr_scheduler_warmup_steps: 20
- num_epochs: 10
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---:|
| 0.6124        | 1.0   | 27   | 0.5658          | 0.75     | 1.0       | 0.4286 | 0.6 |
| 0.5354        | 2.0   | 54   | 0.2746          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.2772        | 3.0   | 81   | 0.2040          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.3967        | 4.0   | 108  | 0.2037          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.3336        | 5.0   | 135  | 0.2289          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.2011        | 6.0   | 162  | 0.2000          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.1995        | 7.0   | 189  | 0.2019          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.1997        | 8.0   | 216  | 0.2025          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.3512        | 9.0   | 243  | 0.2019          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.3142        | 10.0  | 270  | 0.2022          | 1.0      | 1.0       | 1.0    | 1.0 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2