Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_weight_decay_0.007.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: 0.02513178437948227
Inter Cos: 0.10349033027887344
Norm Quadratic Average: 30.38138771057129
Nearest Class Center Accuracy: 0.305875

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03453836962580681
Inter Cos: 0.11468785256147385
Norm Quadratic Average: 22.763696670532227
Nearest Class Center Accuracy: 0.3625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04118506982922554
Inter Cos: 0.11686505377292633
Norm Quadratic Average: 24.10219383239746
Nearest Class Center Accuracy: 0.416125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05577220395207405
Inter Cos: 0.13910368084907532
Norm Quadratic Average: 13.712159156799316
Nearest Class Center Accuracy: 0.443875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07374916970729828
Inter Cos: 0.1567765325307846
Norm Quadratic Average: 10.651748657226562
Nearest Class Center Accuracy: 0.478

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10305047780275345
Inter Cos: 0.17780956625938416
Norm Quadratic Average: 5.1548566818237305
Nearest Class Center Accuracy: 0.5365

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.16295748949050903
Inter Cos: 0.1980728954076767
Norm Quadratic Average: 3.3265414237976074
Nearest Class Center Accuracy: 0.73825

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.50022888183594
Linear Weight Rank: 4031
Intra Cos: 0.4612273573875427
Inter Cos: 0.4146955609321594
Norm Quadratic Average: 15.304094314575195
Nearest Class Center Accuracy: 0.962375

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.398605346679688
Linear Weight Rank: 3671
Intra Cos: 0.691864013671875
Inter Cos: 0.5746275782585144
Norm Quadratic Average: 15.913549423217773
Nearest Class Center Accuracy: 0.997375

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.078326940536499
Linear Weight Rank: 10
Intra Cos: 0.762771487236023
Inter Cos: 0.6645843982696533
Norm Quadratic Average: 19.74178123474121
Nearest Class Center Accuracy: 0.99925

Output Layer:
Intra Cos: 0.8108064532279968
Inter Cos: 0.8102019429206848
Norm Quadratic Average: 26.365358352661133
Nearest Class Center Accuracy: 0.995125

Test Set:
Average Loss: 2.2637435989379884
Accuracy: 0.58
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.25365662574768066, Weights: 0.05600529909133911
NC2 Equiangle: Features: 0.44891365898980035, Weights: 0.21658191680908204
NC3 Self-Duality: 0.3749125003814697
NC4 NCC Mismatch: 0.16500000000000004

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: 0.024210715666413307
Inter Cos: 0.09722906351089478
Norm Quadratic Average: 30.268972396850586
Nearest Class Center Accuracy: 0.329

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036085233092308044
Inter Cos: 0.11042124778032303
Norm Quadratic Average: 22.676868438720703
Nearest Class Center Accuracy: 0.38

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.041677042841911316
Inter Cos: 0.106266550719738
Norm Quadratic Average: 24.03236198425293
Nearest Class Center Accuracy: 0.4355

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05401572212576866
Inter Cos: 0.1240629106760025
Norm Quadratic Average: 13.655673027038574
Nearest Class Center Accuracy: 0.461

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06954488158226013
Inter Cos: 0.13813963532447815
Norm Quadratic Average: 10.619109153747559
Nearest Class Center Accuracy: 0.473

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08634015172719955
Inter Cos: 0.15796230733394623
Norm Quadratic Average: 5.134130477905273
Nearest Class Center Accuracy: 0.4865

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10613830387592316
Inter Cos: 0.17468483746051788
Norm Quadratic Average: 3.287781000137329
Nearest Class Center Accuracy: 0.535

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.50022888183594
Linear Weight Rank: 4031
Intra Cos: 0.19876207411289215
Inter Cos: 0.3336615264415741
Norm Quadratic Average: 14.581274032592773
Nearest Class Center Accuracy: 0.587

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.398605346679688
Linear Weight Rank: 3671
Intra Cos: 0.2588941156864166
Inter Cos: 0.45663461089134216
Norm Quadratic Average: 14.805391311645508
Nearest Class Center Accuracy: 0.588

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.078326940536499
Linear Weight Rank: 10
Intra Cos: 0.26929208636283875
Inter Cos: 0.5323506593704224
Norm Quadratic Average: 18.27652931213379
Nearest Class Center Accuracy: 0.5715

Output Layer:
Intra Cos: 0.2870784401893616
Inter Cos: 0.6543174386024475
Norm Quadratic Average: 24.20250701904297
Nearest Class Center Accuracy: 0.535

