Federated Learning on CIFAR-100 (alpha=0.5, 5 clients per round)

Metric: ACC@1-100Clients (higher is better)

LeaderboardDataset

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#	Model↕	ACC@1-100Clients▼	Augmentations	Paper	Date↕	Code
1	FedASAM + SWA	49.17	No	Improving Generalization in Federated Learning b...	2022-03-22	Code
2	FedSAM + SWA	47.96	No	Improving Generalization in Federated Learning b...	2022-03-22	Code
3	FedASAM	45.61	No	Improving Generalization in Federated Learning b...	2022-03-22	Code
4	FedSAM	44.73	No	Improving Generalization in Federated Learning b...	2022-03-22	Code
5	FedAvg	40.43	No	Improving Generalization in Federated Learning b...	2022-03-22	Code

#1FedASAM + SWASOTA
49.17
ACC@1-100Clients· 2022-03-22
Improving Generalization in Federated Learning by Seeking Flat Minima Code
#2FedSAM + SWA
47.96
ACC@1-100Clients· 2022-03-22
Improving Generalization in Federated Learning by Seeking Flat Minima Code
#3FedASAM
45.61
ACC@1-100Clients· 2022-03-22
Improving Generalization in Federated Learning by Seeking Flat Minima Code
#4FedSAM
44.73
ACC@1-100Clients· 2022-03-22
Improving Generalization in Federated Learning by Seeking Flat Minima Code
#5FedAvg
40.43
ACC@1-100Clients· 2022-03-22
Improving Generalization in Federated Learning by Seeking Flat Minima Code