Federated Learning on CIFAR-100 (alpha=1000, 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	54.81	No	Improving Generalization in Federated Learning b...	2022-03-22	Code
2	FedSAM	54.01	No	Improving Generalization in Federated Learning b...	2022-03-22	Code
3	FedSAM + SWA	53.9	No	Improving Generalization in Federated Learning b...	2022-03-22	Code
4	FedASAM + SWA	53.86	No	Improving Generalization in Federated Learning b...	2022-03-22	Code
5	FedAvg	49.92	No	Improving Generalization in Federated Learning b...	2022-03-22	Code

#1FedASAMSOTA
54.81
ACC@1-100Clients· 2022-03-22
Improving Generalization in Federated Learning by Seeking Flat Minima Code
#2FedSAM
54.01
ACC@1-100Clients· 2022-03-22
Improving Generalization in Federated Learning by Seeking Flat Minima Code
#3FedSAM + SWA
53.9
ACC@1-100Clients· 2022-03-22
Improving Generalization in Federated Learning by Seeking Flat Minima Code
#4FedASAM + SWA
53.86
ACC@1-100Clients· 2022-03-22
Improving Generalization in Federated Learning by Seeking Flat Minima Code
#5FedAvg
49.92
ACC@1-100Clients· 2022-03-22
Improving Generalization in Federated Learning by Seeking Flat Minima Code