---
base_model: openai-community/roberta-large-openai-detector
library_name: transformers
license: mit
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: phishing-binary-classification
  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-binary-classification

This model is a fine-tuned version of [openai-community/roberta-large-openai-detector](https://huggingface.co/openai-community/roberta-large-openai-detector) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2813
- Accuracy: 0.882
- Auc: 0.954

## 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   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----:|
| 0.5501        | 1.0   | 1250  | 0.4015          | 0.818    | 0.927 |
| 0.4611        | 2.0   | 2500  | 0.3605          | 0.842    | 0.923 |
| 0.4445        | 3.0   | 3750  | 0.3759          | 0.827    | 0.939 |
| 0.413         | 4.0   | 5000  | 0.3058          | 0.866    | 0.946 |
| 0.4152        | 5.0   | 6250  | 0.3554          | 0.837    | 0.953 |
| 0.4086        | 6.0   | 7500  | 0.2908          | 0.874    | 0.949 |
| 0.4057        | 7.0   | 8750  | 0.3338          | 0.853    | 0.946 |
| 0.3966        | 8.0   | 10000 | 0.2807          | 0.88     | 0.953 |
| 0.3961        | 9.0   | 11250 | 0.2836          | 0.878    | 0.952 |
| 0.3962        | 10.0  | 12500 | 0.2813          | 0.882    | 0.954 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0