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Few Shot Image Classification On Imagenet 10
Metriken
Top 1 Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| MAWS (ViT-6.5B) | 84.6 | The effectiveness of MAE pre-pretraining for billion-scale pretraining | |
| ViT-MoE-15B (Every-2) | 84.29 | Scaling Vision with Sparse Mixture of Experts | |
| MAWS (ViT-2B) | 83.7 | The effectiveness of MAE pre-pretraining for billion-scale pretraining | |
| MAWS (ViT-H) | 82.5 | The effectiveness of MAE pre-pretraining for billion-scale pretraining | |
| V-MoE-H/14 (Every-2) | 80.33 | Scaling Vision with Sparse Mixture of Experts | |
| V-MoE-H/14 (Last-5) | 80.1 | Scaling Vision with Sparse Mixture of Experts | |
| VIT-H/14 | 79.01 | Scaling Vision with Sparse Mixture of Experts |
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