Image Classification on Tiny-ImageNet Bucket 20 Retain
84.87AccuracyOriginal
Evaluation Results
| Method | Links | |
|---|---|---|
| OriginalEvaluation Head=Linear Probe, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 84.87 | |
| OriginalEvaluation Head=Output, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 84.81 | |
| Retain-only RetainEvaluation Head=Linear Probe, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 84.45 | |
| Retain-only RetainEvaluation Head=Output, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 84.14 | |
| OriginalEvaluation Head=NCC, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 83.49 | |
| Retain-only RetainEvaluation Head=NCC, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 82.74 | |
| Salun with CMFEvaluation Head=Linear Probe, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 81.36 | |
| Random-label with CMFEvaluation Head=Linear Probe, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 80.57 | |
| Salun with CMFEvaluation Head=Output, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 78.34 | |
| Random-label with CMFEvaluation Head=Output, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 78.12 | |
| Salun with CMFEvaluation Head=NCC, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 77.84 | |
| Random-label with CMFEvaluation Head=NCC, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 77.55 | |
| NegGrad+ with CMFEvaluation Head=Linear Probe, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 69.65 | |
| NegGrad+ with CMFEvaluation Head=Output, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 65.38 | |
| NegGrad+ with CMFEvaluation Head=NCC, Backbone=ViT-S/16, Pre-training=ImageNet2026.04 | 63.65 |