vulnerabilityDetection-StarEncoder-Devign – AI Model by neuralsentry | AlphaNeural AI

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neuralsentry/
vulnerabilityDetection-StarEncoder-Devign

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text-classification

generated_from_trainer

bigcode/starencoder

autotrain_compatible

endpoints_compatible

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starencoder-vd-25-75

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

Loss: 0.7599
Accuracy: 0.7019
Precision: 0.7660
Recall: 0.5883
F1: 0.6655
Roc Auc: 0.7028

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: 9e-06
train_batch_size: 45
eval_batch_size: 45
seed: 420
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Roc Auc
0.6213	1.0	551	0.5820	0.6628	0.6816	0.6212	0.6500	0.6631
0.5585	2.0	1102	0.5802	0.6690	0.7861	0.4715	0.5895	0.6706
0.5109	3.0	1653	0.5687	0.6886	0.7681	0.5474	0.6393	0.6897
0.4645	4.0	2204	0.5875	0.6973	0.7742	0.5640	0.6526	0.6984
0.4161	5.0	2755	0.5819	0.7097	0.7425	0.6491	0.6926	0.7101
0.3756	6.0	3306	0.6319	0.7058	0.7451	0.6327	0.6843	0.7064
0.3451	7.0	3857	0.6542	0.7025	0.7358	0.6394	0.6842	0.7030
0.3144	8.0	4408	0.7204	0.7017	0.7607	0.5955	0.6680	0.7025
0.2978	9.0	4959	0.7168	0.7032	0.7524	0.6130	0.6756	0.7040
0.2757	10.0	5510	0.7599	0.7019	0.7660	0.5883	0.6655	0.7028

Framework versions

Transformers 4.31.0
Pytorch 2.1.0.dev20230605+cu121
Datasets 2.14.0
Tokenizers 0.13.3