bert-phishing-classifier – AI Model by maksymstefanko | AlphaNeural AI

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maksymstefanko/
bert-phishing-classifier

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

text-embeddings-inference

endpoints_compatible

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bert-phishing-classifier

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

Loss: 0.3065
Accuracy: 0.884
Auc: 0.945

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: 0.0002
train_batch_size: 8
eval_batch_size: 8
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
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Auc
0.5026	1.0	263	0.3658	0.858	0.926
0.4089	2.0	526	0.3354	0.867	0.934
0.3545	3.0	789	0.3255	0.884	0.936
0.3583	4.0	1052	0.3569	0.867	0.939
0.3515	5.0	1315	0.3576	0.862	0.943
0.3472	6.0	1578	0.3094	0.887	0.942
0.3352	7.0	1841	0.3061	0.887	0.943
0.3122	8.0	2104	0.3037	0.889	0.944
0.3150	9.0	2367	0.3031	0.893	0.945
0.3156	10.0	2630	0.3065	0.884	0.945

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2