Instructions to use syedalvi/fyp-electra-xss-detector-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syedalvi/fyp-electra-xss-detector-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="syedalvi/fyp-electra-xss-detector-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("syedalvi/fyp-electra-xss-detector-v2") model = AutoModelForSequenceClassification.from_pretrained("syedalvi/fyp-electra-xss-detector-v2") - Notebooks
- Google Colab
- Kaggle
fyp-electra-xss-detector-v2
This model is a fine-tuned version of google/electra-base-discriminator on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0197
- Accuracy: 0.9967
- Precision: 1.0
- Recall: 0.9942
- F1: 0.9971
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: 16
- eval_batch_size: 32
- 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: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0373 | 1.0 | 168 | 0.0345 | 0.9933 | 1.0 | 0.9884 | 0.9942 |
| 0.0171 | 2.0 | 336 | 0.0276 | 0.9933 | 1.0 | 0.9884 | 0.9942 |
| 0.0093 | 3.0 | 504 | 0.0083 | 0.9967 | 1.0 | 0.9942 | 0.9971 |
| 0.0012 | 4.0 | 672 | 0.0198 | 0.9967 | 1.0 | 0.9942 | 0.9971 |
| 0.0085 | 5.0 | 840 | 0.0197 | 0.9967 | 1.0 | 0.9942 | 0.9971 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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Model tree for syedalvi/fyp-electra-xss-detector-v2
Base model
google/electra-base-discriminator