Image Classification on Vision Datasets 20 tasks 1.0 (test)
88.9Average AccuracyISO-CLS TA
Evaluation Results
| Method | Links | |
|---|---|---|
| ISO-CLS TABackbone=ViT-L/142025.11 | 88.9 | |
| MDA TABackbone=ViT-L/142025.11 | 88.4 | |
| TSV TABackbone=ViT-L/142025.11 | 87.1 | |
| ISO TABackbone=ViT-L/142025.11 | 87 | |
| ISO-CLS TABackbone=ViT-B/162025.11 | 82.8 | |
| MDA TABackbone=ViT-B/162025.11 | 82.7 | |
| DOGE TABackbone=ViT-L/142025.11 | 81 | |
| TSV TABackbone=ViT-B/162025.11 | 80.5 | |
| ISO TABackbone=ViT-B/162025.11 | 79.5 | |
| DOGE TABackbone=ViT-B/162025.11 | 79.1 | |
| Consensus TABackbone=ViT-L/142025.11 | 78.9 | |
| MDA TABackbone=ViT-B/322025.11 | 77.3 | |
| Consensus TIESBackbone=ViT-L/142025.11 | 76.8 | |
| ISO-CLS TABackbone=ViT-B/322025.11 | 76.6 | |
| TSV TABackbone=ViT-B/322025.11 | 76.4 | |
| Ties-MergingBackbone=ViT-L/142025.11 | 75.7 | |
| Task ArithmeticBackbone=ViT-L/142025.11 | 74 | |
| ISO TABackbone=ViT-B/322025.11 | 73.1 | |
| DOGE TABackbone=ViT-B/322025.11 | 72.5 | |
| Weight averagingBackbone=ViT-L/142025.11 | 71.5 | |
| EvoGMBackbone=ViT-B-16, Number of Experts=20, Iteration Budget=62026.05 | 70.06 | |
| Consensus TABackbone=ViT-B/162025.11 | 69.7 | |
| Ties-MergingBackbone=ViT-B/162025.11 | 68.2 | |
| Consensus TIESBackbone=ViT-B/162025.11 | 67.1 | |
| Task ArithmeticBackbone=ViT-B/162025.11 | 65.9 | |
| Consensus TABackbone=ViT-B/322025.11 | 65.4 | |
| Pre-trainedBackbone=ViT-L/142025.11 | 65.1 | |
| Ties-MergingBackbone=ViT-B/322025.11 | 63.4 | |
| Consensus TIESBackbone=ViT-B/322025.11 | 63.2 | |
| Weight averagingBackbone=ViT-B/162025.11 | 63.1 | |
| Weight averagingBackbone=ViT-B/322025.11 | 61.1 | |
| Task ArithmeticBackbone=ViT-B/322025.11 | 60.6 | |
| Pre-trainedBackbone=ViT-B/162025.11 | 59.8 | |
| Pre-trainedBackbone=ViT-B/322025.11 | 56.1 | |
| CMA-ESBackbone=ViT-B-16, Number of Experts=20, Iteration Budget=62026.05 | 50.28 |