Model save path: ./New_Models/bn_True_dataset_CIFAR100_epochs_200_lr_0.01_model_type_vgg11_rand_seed_979323_test_samples_None_train_samples_None_weight_decay_0.001.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022893190383911133
Inter Cos: 0.07011394202709198
Norm Quadratic Average: 29.326318740844727
Nearest Class Center Accuracy: 0.03258

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02573489025235176
Inter Cos: 0.02651885896921158
Norm Quadratic Average: 19.90171241760254
Nearest Class Center Accuracy: 0.0493

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022087452933192253
Inter Cos: 0.022414816543459892
Norm Quadratic Average: 10.46172046661377
Nearest Class Center Accuracy: 0.06116

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.017575720325112343
Inter Cos: 0.019021160900592804
Norm Quadratic Average: 8.209492683410645
Nearest Class Center Accuracy: 0.06922

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023164747282862663
Inter Cos: 0.020674148574471474
Norm Quadratic Average: 5.631739616394043
Nearest Class Center Accuracy: 0.07882

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025273943319916725
Inter Cos: 0.02379206009209156
Norm Quadratic Average: 4.1516594886779785
Nearest Class Center Accuracy: 0.0853

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06906837224960327
Inter Cos: 0.04433164745569229
Norm Quadratic Average: 2.9259426593780518
Nearest Class Center Accuracy: 0.09762

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.31161069869995117
Inter Cos: 0.12042270600795746
Norm Quadratic Average: 1.6946905851364136
Nearest Class Center Accuracy: 0.0999

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 7.389034748077393
Linear Weight Rank: 4020
Intra Cos: 0.7426297068595886
Inter Cos: 0.22199776768684387
Norm Quadratic Average: 37.97981262207031
Nearest Class Center Accuracy: 0.1

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 6.9531989097595215
Linear Weight Rank: 3519
Intra Cos: 0.8521547913551331
Inter Cos: 0.31275421380996704
Norm Quadratic Average: 31.388748168945312
Nearest Class Center Accuracy: 0.1

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 6.776544094085693
Linear Weight Rank: 98
Intra Cos: 0.8685930967330933
Inter Cos: 0.352509468793869
Norm Quadratic Average: 31.153404235839844
Nearest Class Center Accuracy: 0.1

Output Layer:
Intra Cos: 0.8928042054176331
Inter Cos: 0.4147701561450958
Norm Quadratic Average: 37.8975830078125
Nearest Class Center Accuracy: 0.1

Test Set:
Average Loss: 2.0600806957244875
Accuracy: 0.5566
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.24691997468471527, Weights: 0.027590863406658173
NC2 Equiangle: Features: 0.18736529109453914, Weights: 0.10701366694286617
NC3 Self-Duality: 0.3774099051952362
NC4 NCC Mismatch: 0.15690000000000004

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.006621268577873707
Inter Cos: 0.4067547619342804
Norm Quadratic Average: 29.42218780517578
Nearest Class Center Accuracy: 0.1136

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.013178796507418156
Inter Cos: 0.24944531917572021
Norm Quadratic Average: 20.041431427001953
Nearest Class Center Accuracy: 0.2674

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.015915974974632263
Inter Cos: 0.20397232472896576
Norm Quadratic Average: 10.540292739868164
Nearest Class Center Accuracy: 0.3958

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.013487367890775204
Inter Cos: 0.14125840365886688
Norm Quadratic Average: 8.247937202453613
Nearest Class Center Accuracy: 0.5095

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.012858078815042973
Inter Cos: 0.13372214138507843
Norm Quadratic Average: 5.6447272300720215
Nearest Class Center Accuracy: 0.6035

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.011599809862673283
Inter Cos: 0.11362040787935257
Norm Quadratic Average: 4.1354289054870605
Nearest Class Center Accuracy: 0.6562

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02112802490592003
Inter Cos: 0.16566094756126404
Norm Quadratic Average: 2.8623225688934326
Nearest Class Center Accuracy: 0.6503

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05630279704928398
Inter Cos: 0.3324597179889679
Norm Quadratic Average: 1.5165112018585205
Nearest Class Center Accuracy: 0.5972

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 7.389034748077393
Linear Weight Rank: 4020
Intra Cos: 0.18770496547222137
Inter Cos: 0.45190685987472534
Norm Quadratic Average: 30.301204681396484
Nearest Class Center Accuracy: 0.5564

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 6.9531989097595215
Linear Weight Rank: 3519
Intra Cos: 0.21100342273712158
Inter Cos: 0.48157334327697754
Norm Quadratic Average: 24.72504997253418
Nearest Class Center Accuracy: 0.5584

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 6.776544094085693
Linear Weight Rank: 98
Intra Cos: 0.20997904241085052
Inter Cos: 0.5087227821350098
Norm Quadratic Average: 25.01435089111328
Nearest Class Center Accuracy: 0.5563

Output Layer:
Intra Cos: 0.21702660620212555
Inter Cos: 0.5604158639907837
Norm Quadratic Average: 30.634456634521484
Nearest Class Center Accuracy: 0.5517

