
I finetuned a RobertaForSequenceClassification model which is initialized 
from CodeBert [https://huggingface.co/microsoft/codebert-base] to judge whether a code is vulnerable or not.
I selected balanced samples from MSR dataset [https://github.com/ZeoVan/MSR_20_Code_vulnerability_CSV_Dataset] for training, validation, and testing.
The "func_before" is used for code classification. All the data is in the file "msr.csv".

Test Reulsts: 
acc 0.7022935779816514, f1 0.6482384823848238,  precision 0.7920529801324503, recall 0.5486238532110091
{"license": "mit", "tags": ["Text Classification", "Transformers", "PyTorch", "JAX", "MSR", "English", "roberta", "Inference Endpoints"], "metrics": ["accuracy"], "pipeline_tag": "text-classification"}
transformers pytorch jax safetensors roberta text-classification Text Classification Transformers PyTorch JAX MSR English Inference Endpoints license:mit autotrain_compatible endpoints_compatible region:us