Using model VGG16
Loading dataset CIFAR100 from /data/swa_gaussian/cifar100_data/
Files already downloaded and verified
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Preparing model
Loading model ./cifar100_VGGModel/swag-300.pt
10000
1/30
NLL, Accuracy:  69.28999999999999 1.4859979583942529
2/30
NLL, Accuracy:  72.59 1.198135561177123
3/30
NLL, Accuracy:  73.26 1.1388645130501718
4/30
NLL, Accuracy:  73.65 1.0839078435773384
5/30
NLL, Accuracy:  73.88 1.0486247573416472
6/30
NLL, Accuracy:  73.92999999999999 1.0277511179900516
7/30
NLL, Accuracy:  74.09 1.0099146069397162
8/30
NLL, Accuracy:  73.96000000000001 1.0049361790347455
9/30
NLL, Accuracy:  73.98 0.9942546284083242
10/30
NLL, Accuracy:  73.97 0.9946211865908122
11/30
NLL, Accuracy:  74.19 0.9838590702004217
12/30
NLL, Accuracy:  74.29 0.9795830171837957
13/30
NLL, Accuracy:  74.39 0.9759468700108275
14/30
NLL, Accuracy:  74.28 0.9720715027367213
15/30
NLL, Accuracy:  74.3 0.9689212577566252
16/30
NLL, Accuracy:  74.36 0.962529159226598
17/30
NLL, Accuracy:  74.44 0.95755646056964
18/30
NLL, Accuracy:  74.44 0.9576523140183019
19/30
NLL, Accuracy:  74.53999999999999 0.9587421626995212
20/30
NLL, Accuracy:  74.59 0.9547310519400786
21/30
NLL, Accuracy:  74.6 0.9507360573479753
22/30
NLL, Accuracy:  74.57000000000001 0.9485163256029427
23/30
NLL, Accuracy:  74.64 0.9468923224556116
24/30
NLL, Accuracy:  74.7 0.9463602694234243
25/30
NLL, Accuracy:  74.72999999999999 0.9448532022071606
26/30
NLL, Accuracy:  74.72 0.9401105961675831
27/30
NLL, Accuracy:  74.57000000000001 0.9401539873065374
28/30
NLL, Accuracy:  74.7 0.940097982851225
29/30
NLL, Accuracy:  74.64 0.93986167980163
30/30
NLL, Accuracy:  0.9391126243002371	74.65 
Mean NLL, Mean Accuracy:  1.003176542210368 74.09799999999998
NLL Std, Accuracy Std:  0.10777149974223321 1.0077115989541197
NLL Var, Accuracy Var:  0.011614696156690174 1.0154826666666685