vuln-cat-secbert

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

• Loss: 0.6754
• Accuracy: 0.8977

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: 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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	110	0.5211	0.8886
No log	2.0	220	0.5437	0.8932
No log	3.0	330	0.5760	0.8909
No log	4.0	440	0.6122	0.8955
0.103	5.0	550	0.6467	0.8932
0.103	6.0	660	0.6633	0.8977
0.103	7.0	770	0.6719	0.8977
0.103	8.0	880	0.6754	0.8977

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2