bert-large-finetuned-phishing-webpage-cleaned-version – AI Model by huynq3Cyradar | AlphaNeural AI

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huynq3Cyradar/
bert-large-finetuned-phishing-webpage-cleaned-version

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text-classification

generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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bert-large-finetuned-phishing-webpage-cleaned-version

This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0324
Accuracy: 0.9911
Precision: 0.9931
Recall: 0.9883
False Positive Rate: 0.0063

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
gradient_accumulation_steps: 8
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	False Positive Rate
0.0931	1.0	562	0.0409	0.9861	0.9948	0.9762	0.0047
0.0345	2.0	1124	0.0348	0.9900	0.9918	0.9874	0.0075
0.0224	3.0	1687	0.0324	0.9911	0.9931	0.9883	0.0063
0.0156	4.0	2248	0.0509	0.9913	0.9914	0.9904	0.0079

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2