Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_weight_decay_0.003.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450398489832878
Inter Cos: 0.11371058225631714
Norm Quadratic Average: 27.691619873046875
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023624975234270096
Inter Cos: 0.07784989476203918
Norm Quadratic Average: 76.86722564697266
Nearest Class Center Accuracy: 0.34525

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030347734689712524
Inter Cos: 0.08809014409780502
Norm Quadratic Average: 57.581443786621094
Nearest Class Center Accuracy: 0.372125

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02677682787179947
Inter Cos: 0.06781637668609619
Norm Quadratic Average: 60.24365234375
Nearest Class Center Accuracy: 0.4015

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036108240485191345
Inter Cos: 0.08676965534687042
Norm Quadratic Average: 38.831844329833984
Nearest Class Center Accuracy: 0.422125

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03307640925049782
Inter Cos: 0.06455327570438385
Norm Quadratic Average: 39.44785690307617
Nearest Class Center Accuracy: 0.45475

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04623866826295853
Inter Cos: 0.08002382516860962
Norm Quadratic Average: 25.208768844604492
Nearest Class Center Accuracy: 0.5475

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06678786128759384
Inter Cos: 0.08010108768939972
Norm Quadratic Average: 17.877464294433594
Nearest Class Center Accuracy: 0.84525

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 87.80416107177734
Linear Weight Rank: 4031
Intra Cos: 0.198651522397995
Inter Cos: 0.10782970488071442
Norm Quadratic Average: 95.848876953125
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 35.49827575683594
Linear Weight Rank: 3671
Intra Cos: 0.45131823420524597
Inter Cos: 0.2037040889263153
Norm Quadratic Average: 47.34916305541992
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.272444725036621
Linear Weight Rank: 10
Intra Cos: 0.6798011064529419
Inter Cos: 0.30885085463523865
Norm Quadratic Average: 31.638042449951172
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.874547004699707
Inter Cos: 0.4866972863674164
Norm Quadratic Average: 20.6732120513916
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.0098345947265623
Accuracy: 0.6045
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.21411962807178497, Weights: 0.019090233370661736
NC2 Equiangle: Features: 0.43569615681966145, Weights: 0.08668600188361274
NC3 Self-Duality: 0.6001721024513245
NC4 NCC Mismatch: 0.137

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352367371320724
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: 0.023358697071671486
Inter Cos: 0.07215940207242966
Norm Quadratic Average: 76.6743392944336
Nearest Class Center Accuracy: 0.3625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0297261830419302
Inter Cos: 0.08609568327665329
Norm Quadratic Average: 57.449501037597656
Nearest Class Center Accuracy: 0.401

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026261067017912865
Inter Cos: 0.06450793147087097
Norm Quadratic Average: 60.1566162109375
Nearest Class Center Accuracy: 0.4325

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0332682766020298
Inter Cos: 0.08656211942434311
Norm Quadratic Average: 38.74767303466797
Nearest Class Center Accuracy: 0.4395

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02927411161363125
Inter Cos: 0.06440526247024536
Norm Quadratic Average: 39.32463455200195
Nearest Class Center Accuracy: 0.466

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03498639166355133
Inter Cos: 0.07954205572605133
Norm Quadratic Average: 25.08710479736328
Nearest Class Center Accuracy: 0.4915

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.038949429988861084
Inter Cos: 0.07242172211408615
Norm Quadratic Average: 17.708635330200195
Nearest Class Center Accuracy: 0.567

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 87.80416107177734
Linear Weight Rank: 4031
Intra Cos: 0.06670553982257843
Inter Cos: 0.10985337942838669
Norm Quadratic Average: 92.14251708984375
Nearest Class Center Accuracy: 0.626

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 35.49827575683594
Linear Weight Rank: 3671
Intra Cos: 0.1330285221338272
Inter Cos: 0.21482807397842407
Norm Quadratic Average: 43.465023040771484
Nearest Class Center Accuracy: 0.6105

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.272444725036621
Linear Weight Rank: 10
Intra Cos: 0.19858184456825256
Inter Cos: 0.32814347743988037
Norm Quadratic Average: 28.033239364624023
Nearest Class Center Accuracy: 0.5985

Output Layer:
Intra Cos: 0.2700267732143402
Inter Cos: 0.4728236794471741
Norm Quadratic Average: 17.918601989746094
Nearest Class Center Accuracy: 0.5735

