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bert-base-uncased-phishing-classification – AI Model by jmmrcp | AlphaNeural AI
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jmmrcp
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bert-base-uncased-phishing-classification
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tensorboard
safetensors
bert
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
us
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phishing-IBM
This model is a fine-tuned version of
google-bert/bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0249
Accuracy: 0.9954
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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Framework versions
Transformers 4.44.0
Pytorch 2.4.0
Datasets 2.21.0
Tokenizers 0.19.1
