Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_weight_decay_0.03.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450400352478027
Inter Cos: 0.11371058970689774
Norm Quadratic Average: 27.691621780395508
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028442498296499252
Inter Cos: 0.1056608185172081
Norm Quadratic Average: 12.862309455871582
Nearest Class Center Accuracy: 0.322125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03377961739897728
Inter Cos: 0.11930926889181137
Norm Quadratic Average: 5.184136867523193
Nearest Class Center Accuracy: 0.384625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06952069699764252
Inter Cos: 0.23452256619930267
Norm Quadratic Average: 5.289831638336182
Nearest Class Center Accuracy: 0.384875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.11073832213878632
Inter Cos: 0.3536803126335144
Norm Quadratic Average: 4.973058700561523
Nearest Class Center Accuracy: 0.369625

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.16521631181240082
Inter Cos: 0.4419666528701782
Norm Quadratic Average: 6.0276713371276855
Nearest Class Center Accuracy: 0.362

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.22898927330970764
Inter Cos: 0.5239813327789307
Norm Quadratic Average: 5.261796474456787
Nearest Class Center Accuracy: 0.3705

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.23398669064044952
Inter Cos: 0.5484603047370911
Norm Quadratic Average: 4.172259330749512
Nearest Class Center Accuracy: 0.3935

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.99199104309082
Linear Weight Rank: 4031
Intra Cos: 0.23936116695404053
Inter Cos: 0.5684526562690735
Norm Quadratic Average: 18.086084365844727
Nearest Class Center Accuracy: 0.4145

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.78130054473877
Linear Weight Rank: 3671
Intra Cos: 0.2507016956806183
Inter Cos: 0.5930665731430054
Norm Quadratic Average: 11.608152389526367
Nearest Class Center Accuracy: 0.42

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.514093279838562
Linear Weight Rank: 10
Intra Cos: 0.28663361072540283
Inter Cos: 0.6309327483177185
Norm Quadratic Average: 7.64943790435791
Nearest Class Center Accuracy: 0.420625

Output Layer:
Intra Cos: 0.32623475790023804
Inter Cos: 0.7097671031951904
Norm Quadratic Average: 5.937856674194336
Nearest Class Center Accuracy: 0.39125

Test Set:
Average Loss: 1.505012596130371
Accuracy: 0.41
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.25900599360466003, Weights: 0.10676563531160355
NC2 Equiangle: Features: 0.774551984998915, Weights: 0.27897184160020616
NC3 Self-Duality: 0.4306362271308899
NC4 NCC Mismatch: 0.28600000000000003

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
Inter Cos: 0.09352368116378784
Norm Quadratic Average: 27.530664443969727
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027443932369351387
Inter Cos: 0.0982479378581047
Norm Quadratic Average: 12.811264991760254
Nearest Class Center Accuracy: 0.3435

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03524186834692955
Inter Cos: 0.10684820264577866
Norm Quadratic Average: 5.137423038482666
Nearest Class Center Accuracy: 0.394

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06162725016474724
Inter Cos: 0.22615580260753632
Norm Quadratic Average: 5.23081111907959
Nearest Class Center Accuracy: 0.4045

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09006007760763168
Inter Cos: 0.3457566201686859
Norm Quadratic Average: 4.923166275024414
Nearest Class Center Accuracy: 0.3695

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.13498170673847198
Inter Cos: 0.43815818428993225
Norm Quadratic Average: 5.980085849761963
Nearest Class Center Accuracy: 0.3515

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18492615222930908
Inter Cos: 0.524445116519928
Norm Quadratic Average: 5.235385894775391
Nearest Class Center Accuracy: 0.353

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.219790518283844
Inter Cos: 0.5522947907447815
Norm Quadratic Average: 4.1581830978393555
Nearest Class Center Accuracy: 0.3815

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.99199104309082
Linear Weight Rank: 4031
Intra Cos: 0.2455551028251648
Inter Cos: 0.5750299692153931
Norm Quadratic Average: 18.07353401184082
Nearest Class Center Accuracy: 0.405

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.78130054473877
Linear Weight Rank: 3671
Intra Cos: 0.2701054811477661
Inter Cos: 0.603509783744812
Norm Quadratic Average: 11.633070945739746
Nearest Class Center Accuracy: 0.411

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.514093279838562
Linear Weight Rank: 10
Intra Cos: 0.3146548271179199
Inter Cos: 0.6477887034416199
Norm Quadratic Average: 7.687002182006836
Nearest Class Center Accuracy: 0.4145

Output Layer:
Intra Cos: 0.38474205136299133
Inter Cos: 0.7361363768577576
Norm Quadratic Average: 5.979404449462891
Nearest Class Center Accuracy: 0.392

