Generalization gap prediction on QNLI
0.14Generalization Gap Error1-sharpness
Evaluation Results
| Method | Links | |
|---|---|---|
| 1-sharpnessTraining scenario=Fine-tuning, Data source=Test loss landscape (dev data, unfair advantage)2023.05 | 0.14 | |
| HessianTraining scenario=Fine-tuning, Data source=Test loss landscape (dev data, unfair advantage)2023.05 | 0.15 | |
| InconsistencyTraining scenario=Fine-tuning, Data source=Unlabeled data2023.05 | 0.19 | |
| 1-sharpnessTraining scenario=Fine-tuning, Data source=Training loss landscape2023.05 | 0.24 | |
| HessianTraining scenario=Fine-tuning, Data source=Training loss landscape2023.05 | 0.68 |