Inconsistency in pretrained mae vitb16 weights

[jafarinia]

Hi
I have a question about your pretreined mae vitb16 weights.
When I use "https://github.com/ShoufaChen/AdaptFormer/releases/download/v0.1/mae_pretrain_vit_b.pth" which is the one on your GitHub repo and train on Cifar100 for 1 epoch I generally get
Acc@1 37.330 Acc@5 67.820 loss 2.768
(the command is python main_image.py --batch_size=128 --cls_token --epochs=1 --finetune=mae_pretrain_vit_b.pth --dist_eval
--data_path=cifar100 --output_dir=output --num_workers=16 --drop_path=0.0 --blr=0.1 --dataset=cifar100 --ffn_adapt)
But
When I use "https://dl.fbaipublicfiles.com/mae/pretrain/mae_pretrain_vit_base.pth" which is the claimed weight on your paper's text and train on Cifar100 for 1 epoch I generally get
Acc@1 5.660 Acc@5 21.350 loss 4.295.
(the command is python main_image.py --batch_size=128 --cls_token --epochs=1 --finetune=mae_pretrain_vit_base.pth --dist_e
val --data_path=cifar100 --output_dir=output --num_workers=16 --drop_path=0.0 --blr=0.1 --dataset=cifar100 --ffn_adapt)
These results are consistent over multiple runs.
My questions are, what is the difference between these two pretrained weights? And what causes this huge difference in results?