starencoder-vulnfix-classification

This model is a fine-tuned version of neuralsentry/distilbert-git-commits-mlm on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2247
• Accuracy: 0.9087
• Precision: 0.9401
• Recall: 0.9210
• F1: 0.9304
• Roc Auc: 0.9027

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: 0.0001
• train_batch_size: 256
• eval_batch_size: 256
• seed: 420
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Roc Auc
0.36	1.57	33	0.2265	0.9124	0.9315	0.9368	0.9342	0.9006

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.0
• Tokenizers 0.13.3