semihGuner2002/distilbert-base-uncased-finetuned-URL

This model is a fine-tuned version of distilbert-base-uncased on my own phishing URL dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0065
• Validation Loss: 0.0589
• Epoch: 4

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:

• optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.0}
• training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
0.0733	0.0372	0
0.0339	0.0487	1
0.0191	0.0379	2
0.0103	0.0441	3
0.0065	0.0589	4

Framework versions

• Transformers 4.35.2
• TensorFlow 2.15.0
• Datasets 2.16.1
• Tokenizers 0.15.0