Defect Detection On Codexglue Devign
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy |
|---|---|
| graph-convolutions-enrich-the-self-attention | 62.96 |
| graph-convolutions-enrich-the-self-attention | 63.69 |
| graph-convolutions-enrich-the-self-attention | 63.25 |
| graph-convolutions-enrich-the-self-attention | 64.39 |
| graph-convolutions-enrich-the-self-attention | 62.63 |
| codet5-identifier-aware-unified-pre-trained | 65.78 |
| graph-convolutions-enrich-the-self-attention | 63.51 |
| graph-convolutions-enrich-the-self-attention | 64.49 |
| graph-convolutions-enrich-the-self-attention | 62.88 |
| graph-convolutions-enrich-the-self-attention | 64.31 |
| codexglue-a-machine-learning-benchmark | 62.08 |
| graph-convolutions-enrich-the-self-attention | 64.75 |