Generalization gap prediction on QNLI Case 9
0.18Gap Prediction ErrorInconsistency
Evaluation Results
| Method | Links | |
|---|---|---|
| InconsistencyTraining scenario=Fine-tuning, Data source=Unlabeled data2023.05 | 0.18 | |
| 1-sharpnessTraining scenario=Fine-tuning, Data source=Test loss landscape (dev data, unfair advantage)2023.05 | 0.37 | |
| HessianTraining scenario=Fine-tuning, Data source=Test loss landscape (dev data, unfair advantage)2023.05 | 0.81 | |
| HessianTraining scenario=Fine-tuning, Data source=Training loss landscape2023.05 | 0.87 | |
| 1-sharpnessTraining scenario=Fine-tuning, Data source=Training loss landscape2023.05 | 0.98 |