Image Classification on CIFAR-100 personalized (test)
66.32Client 1 AccuracyPOTARA
Evaluation results
| Method | Links | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| POTARABackbone=ViT-B/162026.02 | 66.32 | 66.55 | 67.26 | 63.43 | 65.86 | 62.93 | 66.37 | 64.6 | 65.15 | 63.68 | 65.21 | |
| FedDPABackbone=ViT-B/162026.02 | 62.8 | 60.51 | 61.22 | 62.41 | 61.54 | 60.31 | 63.24 | 62.09 | 62.74 | 61.14 | 61.8 | |
| FedITBackbone=ViT-B/162026.02 | 62.55 | 60.53 | 60.3 | 59.48 | 62.07 | 59.99 | 61.93 | 62.73 | 63.6 | 59.61 | 61.28 | |
| FedSABackbone=ViT-B/162026.02 | 62.24 | 63.11 | 61.79 | 61.16 | 59.44 | 59.17 | 61.11 | 59.73 | 59.71 | 61.24 | 60.87 | |
| Fish MergingBackbone=ViT-B/162026.02 | 62.19 | 62.08 | 65.29 | 61.65 | 62.54 | 60.89 | 61.53 | 60.85 | 60.4 | 59.78 | 61.72 | |
| LocalBackbone=ViT-B/162026.02 | 60.01 | 59.78 | 63.26 | 61.79 | 61.26 | 56.46 | 60.62 | 61.79 | 58.75 | 60.53 | 60.43 | |
| FFA-LoRABackbone=ViT-B/162026.02 | 39.96 | 44.55 | 42.36 | 40.14 | 42.85 | 38.62 | 41.5 | 40.03 | 44.07 | 41.08 | 41.52 |