metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- text-classification
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: phishing-links-detection-using-transformers
results: []
phishing-links-detection-using-transformers
This model is a fine-tuned version of distilbert-base-uncased on the Razvan27/remla_phishing_url dataset. It achieves the following results on the evaluation set:
- Loss: 0.1545
- Precision: 0.9757
- Recall: 0.9673
- F1: 0.9715
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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: tpu
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.1044 | 1.0 | 3269 | 0.0874 | 0.9688 | 0.9583 | 0.9635 |
| 0.0709 | 2.0 | 6538 | 0.0938 | 0.9603 | 0.9736 | 0.9669 |
| 0.0224 | 3.0 | 9807 | 0.1064 | 0.9781 | 0.9644 | 0.9712 |
| 0.0254 | 4.0 | 13076 | 0.1281 | 0.9768 | 0.9653 | 0.9710 |
| 0.0161 | 5.0 | 16345 | 0.1545 | 0.9757 | 0.9673 | 0.9715 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cpu
- Tokenizers 0.21.1