Baseline_30Kphish_benignFall_20_20_20 – AI Model by AustinCarthy | AlphaNeural AI

You can deploy this model and start earning money today!

AustinCarthy/
Baseline_30Kphish_benignFall_20_20_20

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

Baseline_30Kphish_benignFall_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: 0.0374
Accuracy: 0.9962
F1: 0.9589
Precision: 0.9998
Recall: 0.9212
Roc Auc Score: 0.9606
Tpr At Fpr 0.01: 0.9438

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
0.0045	1.0	19688	0.0304	0.9933	0.9241	0.9993	0.8594	0.9297	0.874
0.0029	2.0	39376	0.0210	0.9967	0.9643	0.9953	0.9352	0.9675	0.917
0.0003	3.0	59064	0.0434	0.9947	0.9407	0.9980	0.8896	0.9448	0.8936
0.0016	4.0	78752	0.0408	0.9952	0.9468	0.9998	0.8992	0.9496	0.9336
0.0008	5.0	98440	0.0374	0.9962	0.9589	0.9998	0.9212	0.9606	0.9438

Framework versions

Transformers 4.29.1
Pytorch 1.9.0+cu111
Datasets 2.10.1
Tokenizers 0.13.2