Baseline_10Kphish_benignWinter_20_20_20 – AI Model by AustinCarthy | AlphaNeural AI

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AustinCarthy/
Baseline_10Kphish_benignWinter_20_20_20

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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Baseline_10Kphish_benignWinter_20_20_20

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

Loss: 0.0869
Accuracy: 0.991
F1: 0.8960
Precision: 0.9966
Recall: 0.8138
Roc Auc Score: 0.9068
Tpr At Fpr 0.01: 0.7918

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Roc Auc Score	Tpr At Fpr 0.01
0.0115	1.0	6563	0.0605	0.9872	0.8462	0.9938	0.7368	0.8683	0.6832
0.006	2.0	13126	0.0538	0.9911	0.8975	0.9946	0.8176	0.9087	0.7928
0.0033	3.0	19689	0.0496	0.9917	0.9049	0.9959	0.8292	0.9145	0.805
0.001	4.0	26252	0.0791	0.9911	0.8970	0.9959	0.816	0.9079	0.7806
0.0002	5.0	32815	0.0869	0.991	0.8960	0.9966	0.8138	0.9068	0.7918

Framework versions

Transformers 4.29.1
Pytorch 1.9.0+cu111
Datasets 2.10.1
Tokenizers 0.13.2