---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: RoBERTa-WebAttack
  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. -->

# RoBERTa-WebAttack

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0133
- F1: 0.9974
- Accuracy: 0.9974
- Precision: 0.9974
- Recall: 0.9974

## 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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Accuracy | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|:---------:|:------:|
| 0.0207        | 1.0   | 3713  | 0.0229          | 0.9956 | 0.9956   | 0.9956    | 0.9956 |
| 0.0215        | 2.0   | 7426  | 0.0158          | 0.9963 | 0.9963   | 0.9963    | 0.9963 |
| 0.001         | 3.0   | 11139 | 0.0133          | 0.9974 | 0.9974   | 0.9974    | 0.9974 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1