Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_weight_decay_0.0003.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: 27.691617965698242
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025711972266435623
Inter Cos: 0.10994262993335724
Norm Quadratic Average: 29.37306022644043
Nearest Class Center Accuracy: 0.319125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028349699452519417
Inter Cos: 0.11414384841918945
Norm Quadratic Average: 23.415748596191406
Nearest Class Center Accuracy: 0.38025

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03637060895562172
Inter Cos: 0.11714756488800049
Norm Quadratic Average: 28.549928665161133
Nearest Class Center Accuracy: 0.42225

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05672445148229599
Inter Cos: 0.15014642477035522
Norm Quadratic Average: 18.402427673339844
Nearest Class Center Accuracy: 0.446125

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07071495056152344
Inter Cos: 0.1573772132396698
Norm Quadratic Average: 17.2213077545166
Nearest Class Center Accuracy: 0.476875

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09026278555393219
Inter Cos: 0.16165044903755188
Norm Quadratic Average: 9.564995765686035
Nearest Class Center Accuracy: 0.52425

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.11931154131889343
Inter Cos: 0.1746853142976761
Norm Quadratic Average: 7.160126686096191
Nearest Class Center Accuracy: 0.692125

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.9530258178711
Linear Weight Rank: 4031
Intra Cos: 0.3057314455509186
Inter Cos: 0.2540322542190552
Norm Quadratic Average: 28.452106475830078
Nearest Class Center Accuracy: 0.971125

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.45208740234375
Linear Weight Rank: 3670
Intra Cos: 0.5901600122451782
Inter Cos: 0.4062950611114502
Norm Quadratic Average: 24.63575553894043
Nearest Class Center Accuracy: 0.999125

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.257366895675659
Linear Weight Rank: 10
Intra Cos: 0.7439610362052917
Inter Cos: 0.5144287347793579
Norm Quadratic Average: 28.928138732910156
Nearest Class Center Accuracy: 0.99925

Output Layer:
Intra Cos: 0.8061825633049011
Inter Cos: 0.662498950958252
Norm Quadratic Average: 35.375465393066406
Nearest Class Center Accuracy: 0.996125

Test Set:
Average Loss: 3.113687957763672
Accuracy: 0.608
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.25109773874282837, Weights: 0.043537385761737823
NC2 Equiangle: Features: 0.4196316189236111, Weights: 0.16091931660970052
NC3 Self-Duality: 0.45214909315109253
NC4 NCC Mismatch: 0.138

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
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: 0.025273440405726433
Inter Cos: 0.09379558265209198
Norm Quadratic Average: 29.192272186279297
Nearest Class Center Accuracy: 0.3365

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029569217935204506
Inter Cos: 0.09986347705125809
Norm Quadratic Average: 23.27471923828125
Nearest Class Center Accuracy: 0.397

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03642847388982773
Inter Cos: 0.10366548597812653
Norm Quadratic Average: 28.43814468383789
Nearest Class Center Accuracy: 0.45

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0533844493329525
Inter Cos: 0.1329435110092163
Norm Quadratic Average: 18.326196670532227
Nearest Class Center Accuracy: 0.465

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06353259086608887
Inter Cos: 0.13826841115951538
Norm Quadratic Average: 17.17442512512207
Nearest Class Center Accuracy: 0.4805

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07343820482492447
Inter Cos: 0.13972249627113342
Norm Quadratic Average: 9.52106761932373
Nearest Class Center Accuracy: 0.495

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08393415808677673
Inter Cos: 0.14807170629501343
Norm Quadratic Average: 7.097644329071045
Nearest Class Center Accuracy: 0.5335

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.9530258178711
Linear Weight Rank: 4031
Intra Cos: 0.13431794941425323
Inter Cos: 0.23140853643417358
Norm Quadratic Average: 27.463214874267578
Nearest Class Center Accuracy: 0.605

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.45208740234375
Linear Weight Rank: 3670
Intra Cos: 0.21038872003555298
Inter Cos: 0.35993102192878723
Norm Quadratic Average: 23.130159378051758
Nearest Class Center Accuracy: 0.6065

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.257366895675659
Linear Weight Rank: 10
Intra Cos: 0.24490080773830414
Inter Cos: 0.45124831795692444
Norm Quadratic Average: 26.896154403686523
Nearest Class Center Accuracy: 0.595

Output Layer:
Intra Cos: 0.2819950580596924
Inter Cos: 0.5650899410247803
Norm Quadratic Average: 32.747039794921875
Nearest Class Center Accuracy: 0.574

