Vulnerability_Detection_Using_CodeBERT – AI Model by RayenLLM | AlphaNeural AI

You can deploy this model and start earning money today!

RayenLLM/
Vulnerability_Detection_Using_CodeBERT

like

0

text-classification

generated_from_trainer

microsoft/codebert-base

autotrain_compatible

endpoints_compatible

Views

No views yet

Vulnerability_Detection_Using_CodeBERT

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

Loss: 0.0740
Accuracy: 1.0
Auc: 1.0
Precision: 1.0

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 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	Precision
0.2971	1.0	26	0.1815	0.925	1.0	0.81
0.2407	2.0	52	0.1349	0.981	1.0	0.944
0.2619	3.0	78	0.1668	0.887	1.0	0.739
0.2207	4.0	104	0.1081	1.0	1.0	1.0
0.1543	5.0	130	0.1037	0.981	1.0	1.0
0.1428	6.0	156	0.0974	0.981	1.0	0.944
0.1598	7.0	182	0.0916	0.981	1.0	1.0
0.1324	8.0	208	0.1024	0.981	1.0	0.944
0.1445	9.0	234	0.0726	1.0	1.0	1.0
0.1287	10.0	260	0.0740	1.0	1.0	1.0

Framework versions

Transformers 4.50.0
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1