Generalization gap prediction on MNLI Case 8
15Gap Prediction ErrorInconsistency
Evaluation results
| Method | Links | |
|---|---|---|
| InconsistencyTraining scenario=Fine-tuning, Data source=Unlabeled data2023.05 | 15 | |
| 1-sharpnessTraining scenario=Fine-tuning, Data source=Test loss landscape (dev data, unfair advantage)2023.05 | 36 | |
| 1-sharpnessTraining scenario=Fine-tuning, Data source=Training loss landscape2023.05 | 58 | |
| HessianTraining scenario=Fine-tuning, Data source=Training loss landscape2023.05 | 59 | |
| HessianTraining scenario=Fine-tuning, Data source=Test loss landscape (dev data, unfair advantage)2023.05 | 91 |