Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_weight_decay_0.02.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: 0.02666820026934147
Inter Cos: 0.10177461057901382
Norm Quadratic Average: 33.37559127807617
Nearest Class Center Accuracy: 0.339125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03195338323712349
Inter Cos: 0.09207876026630402
Norm Quadratic Average: 24.23307228088379
Nearest Class Center Accuracy: 0.374875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027738239616155624
Inter Cos: 0.07311937212944031
Norm Quadratic Average: 26.30590057373047
Nearest Class Center Accuracy: 0.409875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03629625588655472
Inter Cos: 0.07979956269264221
Norm Quadratic Average: 16.681421279907227
Nearest Class Center Accuracy: 0.44275

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0354592464864254
Inter Cos: 0.0693332701921463
Norm Quadratic Average: 17.061132431030273
Nearest Class Center Accuracy: 0.509625

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.061054978519678116
Inter Cos: 0.08837530016899109
Norm Quadratic Average: 10.644030570983887
Nearest Class Center Accuracy: 0.758125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.17476125061511993
Inter Cos: 0.10852175205945969
Norm Quadratic Average: 7.091108322143555
Nearest Class Center Accuracy: 0.999875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.808197021484375
Linear Weight Rank: 4031
Intra Cos: 0.6301574110984802
Inter Cos: 0.20164641737937927
Norm Quadratic Average: 56.806541442871094
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.74089527130127
Linear Weight Rank: 3671
Intra Cos: 0.8932328224182129
Inter Cos: 0.2719176113605499
Norm Quadratic Average: 28.657516479492188
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6924113035202026
Linear Weight Rank: 10
Intra Cos: 0.9382511377334595
Inter Cos: 0.30081990361213684
Norm Quadratic Average: 18.163949966430664
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.948552131652832
Inter Cos: 0.3676292300224304
Norm Quadratic Average: 11.558938026428223
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.3356900520324706
Accuracy: 0.606
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.18091602623462677, Weights: 0.01875338703393936
NC2 Equiangle: Features: 0.390637461344401, Weights: 0.13967115614149306
NC3 Self-Duality: 0.3400721549987793
NC4 NCC Mismatch: 0.12549999999999994

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: 0.024518713355064392
Inter Cos: 0.08939230442047119
Norm Quadratic Average: 33.370506286621094
Nearest Class Center Accuracy: 0.354

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03046310879290104
Inter Cos: 0.08920599520206451
Norm Quadratic Average: 24.231281280517578
Nearest Class Center Accuracy: 0.3975

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02734132669866085
Inter Cos: 0.06867402791976929
Norm Quadratic Average: 26.32919692993164
Nearest Class Center Accuracy: 0.431

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.033597446978092194
Inter Cos: 0.08071866631507874
Norm Quadratic Average: 16.68863296508789
Nearest Class Center Accuracy: 0.4615

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03099791146814823
Inter Cos: 0.06537187844514847
Norm Quadratic Average: 17.059566497802734
Nearest Class Center Accuracy: 0.495

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.038162313401699066
Inter Cos: 0.08214384317398071
Norm Quadratic Average: 10.616464614868164
Nearest Class Center Accuracy: 0.54

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.054615188390016556
Inter Cos: 0.10881642252206802
Norm Quadratic Average: 6.90424919128418
Nearest Class Center Accuracy: 0.6295

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.808197021484375
Linear Weight Rank: 4031
Intra Cos: 0.1494230479001999
Inter Cos: 0.22919654846191406
Norm Quadratic Average: 49.45301818847656
Nearest Class Center Accuracy: 0.6135

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.74089527130127
Linear Weight Rank: 3671
Intra Cos: 0.2399662733078003
Inter Cos: 0.3447260558605194
Norm Quadratic Average: 23.25810432434082
Nearest Class Center Accuracy: 0.6045

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6924113035202026
Linear Weight Rank: 10
Intra Cos: 0.25839173793792725
Inter Cos: 0.38465675711631775
Norm Quadratic Average: 14.645872116088867
Nearest Class Center Accuracy: 0.6005

Output Layer:
Intra Cos: 0.26535046100616455
Inter Cos: 0.4259248971939087
Norm Quadratic Average: 9.288670539855957
Nearest Class Center Accuracy: 0.5955

