Machine Unlearning on Tiny-ImageNet Swin-T (test)
75.72Residual Accuracy
retrained
Updated 4d ago
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
2026.01 | 75.72 | 0 | 0 | |
2026.01 | 75.57 | 0 | 0 | |
2026.01 | 75.08 | 0 | - | |
2026.01 | 74.55 | 69 | 80 | |
2026.01 | 74.54 | 73 | 75.33 | |
2026.01 | 74.53 | 69 | 74.5 | |
2026.01 | 74.49 | 80 | - | |
2026.01 | 74.37 | 1 | 0 | |
2026.01 | 74.34 | 2 | - | |
2026.01 | 73.87 | 0 | - | |
2026.01 | 73.79 | 2 | 0 | |
2026.01 | 73.43 | 9 | 0 | |
2026.01 | 73.06 | 0 | 0 | |
2026.01 | 72.8 | 0 | 0.5 | |
2026.01 | 72.65 | 0 | - | |
2026.01 | 72.58 | 6 | - | |
2026.01 | 72.5 | 3 | 0 | |
2026.01 | 72.4 | 5 | 0 | |
2026.01 | 72.01 | 4 | 1 | |
2026.01 | 70.87 | 1 | - | |
2026.01 | 70.05 | 3 | 1.5 | |
2026.01 | 67.91 | 3 | 1.33 | |
2026.01 | 67.07 | 8 | 3 | |
2026.01 | 59.68 | 2 | 0 | |
2026.01 | 54.42 | 1 | 2.5 | |
2026.01 | 37.69 | 1 | 0.67 | |
2026.01 | 36.27 | 0 | 0.5 | |
2026.01 | 9.97 | 1 | 0 |