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RoBERTa-WebAttack
maleke01/RoBERTa-WebAttack
RoBERTa-WebAttack is a text classification model from maleke01. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Jul 26, 2024
- Updated
- Aug 8, 2024
- SHA
- 9b321eb6
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- 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 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
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jul 26, 2024
- Updated
- Aug 8, 2024