Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_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: 0.021450400352478027
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: 0.023294540122151375
Inter Cos: 0.10026360303163528
Norm Quadratic Average: 84.75768280029297
Nearest Class Center Accuracy: 0.351875

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025455178692936897
Inter Cos: 0.09367451071739197
Norm Quadratic Average: 63.083335876464844
Nearest Class Center Accuracy: 0.37975

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022345462813973427
Inter Cos: 0.06874330341815948
Norm Quadratic Average: 66.90912628173828
Nearest Class Center Accuracy: 0.409625

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02987861819565296
Inter Cos: 0.07864651829004288
Norm Quadratic Average: 42.27411651611328
Nearest Class Center Accuracy: 0.434125

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0301850326359272
Inter Cos: 0.07096049189567566
Norm Quadratic Average: 43.17762756347656
Nearest Class Center Accuracy: 0.47725

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04176747426390648
Inter Cos: 0.0769881010055542
Norm Quadratic Average: 27.537322998046875
Nearest Class Center Accuracy: 0.559

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06438416242599487
Inter Cos: 0.07423672825098038
Norm Quadratic Average: 19.697084426879883
Nearest Class Center Accuracy: 0.841375

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.63504028320312
Linear Weight Rank: 4031
Intra Cos: 0.18476001918315887
Inter Cos: 0.09696737676858902
Norm Quadratic Average: 106.04357147216797
Nearest Class Center Accuracy: 0.99975

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.06742477416992
Linear Weight Rank: 3670
Intra Cos: 0.4254189133644104
Inter Cos: 0.17270848155021667
Norm Quadratic Average: 54.06672286987305
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.448772430419922
Linear Weight Rank: 10
Intra Cos: 0.6628859639167786
Inter Cos: 0.26459211111068726
Norm Quadratic Average: 37.14113235473633
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.877252459526062
Inter Cos: 0.4478875994682312
Norm Quadratic Average: 25.286863327026367
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.5105756149291993
Accuracy: 0.5935
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2035617232322693, Weights: 0.018663281574845314
NC2 Equiangle: Features: 0.43400260077582464, Weights: 0.09024302164713542
NC3 Self-Duality: 0.62385493516922
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: 0.09352368116378784
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: 0.022758610546588898
Inter Cos: 0.08824285119771957
Norm Quadratic Average: 84.39354705810547
Nearest Class Center Accuracy: 0.373

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0250040702521801
Inter Cos: 0.08277533203363419
Norm Quadratic Average: 62.7751350402832
Nearest Class Center Accuracy: 0.407

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021310927346348763
Inter Cos: 0.06065500155091286
Norm Quadratic Average: 66.6655044555664
Nearest Class Center Accuracy: 0.444

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026125406846404076
Inter Cos: 0.07025979459285736
Norm Quadratic Average: 42.08229064941406
Nearest Class Center Accuracy: 0.4525

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026190072298049927
Inter Cos: 0.06305742263793945
Norm Quadratic Average: 43.00224304199219
Nearest Class Center Accuracy: 0.4855

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030547669157385826
Inter Cos: 0.06714586168527603
Norm Quadratic Average: 27.3561954498291
Nearest Class Center Accuracy: 0.4975

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034511126577854156
Inter Cos: 0.07112729549407959
Norm Quadratic Average: 19.49039077758789
Nearest Class Center Accuracy: 0.571

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.63504028320312
Linear Weight Rank: 4031
Intra Cos: 0.06107800081372261
Inter Cos: 0.10736126452684402
Norm Quadratic Average: 102.11393737792969
Nearest Class Center Accuracy: 0.621

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.06742477416992
Linear Weight Rank: 3670
Intra Cos: 0.12434972077608109
Inter Cos: 0.19816221296787262
Norm Quadratic Average: 49.73789596557617
Nearest Class Center Accuracy: 0.6005

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.448772430419922
Linear Weight Rank: 10
Intra Cos: 0.19353581964969635
Inter Cos: 0.3073740601539612
Norm Quadratic Average: 32.84861373901367
Nearest Class Center Accuracy: 0.59

Output Layer:
Intra Cos: 0.28874385356903076
Inter Cos: 0.47788694500923157
Norm Quadratic Average: 21.70694351196289
Nearest Class Center Accuracy: 0.575

