phishing-site-classification

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.4038

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: 1e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use 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: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.4346	1.0	132	0.4356
0.4362	2.0	264	0.4370
0.4238	3.0	396	0.4256
0.3952	4.0	528	0.4198
0.3835	5.0	660	0.4202
0.4115	6.0	792	0.4146
0.4077	7.0	924	0.4172
0.411	8.0	1056	0.4143
0.3726	9.0	1188	0.4135
0.3942	10.0	1320	0.4091
0.4135	11.0	1452	0.4071
0.3817	12.0	1584	0.4091
0.399	13.0	1716	0.4072
0.4087	14.0	1848	0.4035
0.3912	15.0	1980	0.4038

Framework versions

• Transformers 4.57.6
• Pytorch 2.5.1+cu121
• Datasets 4.5.0
• Tokenizers 0.22.2