Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_weight_decay_0.03.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: 0.11371058225631714
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: 0.023613611236214638
Inter Cos: 0.10171619057655334
Norm Quadratic Average: 20.3863582611084
Nearest Class Center Accuracy: 0.334125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02551860548555851
Inter Cos: 0.09122420847415924
Norm Quadratic Average: 15.170886039733887
Nearest Class Center Accuracy: 0.370625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022097891196608543
Inter Cos: 0.06989350914955139
Norm Quadratic Average: 16.17624855041504
Nearest Class Center Accuracy: 0.405125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032448846846818924
Inter Cos: 0.08295288681983948
Norm Quadratic Average: 10.25932788848877
Nearest Class Center Accuracy: 0.436875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034909460693597794
Inter Cos: 0.07516001909971237
Norm Quadratic Average: 10.405029296875
Nearest Class Center Accuracy: 0.526125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07669154554605484
Inter Cos: 0.10028829425573349
Norm Quadratic Average: 6.19215202331543
Nearest Class Center Accuracy: 0.86975

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3730466663837433
Inter Cos: 0.16641904413700104
Norm Quadratic Average: 4.039445877075195
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 24.00110626220703
Linear Weight Rank: 4031
Intra Cos: 0.8853867053985596
Inter Cos: 0.3187287449836731
Norm Quadratic Average: 45.51412582397461
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.79730224609375
Linear Weight Rank: 3669
Intra Cos: 0.9773678183555603
Inter Cos: 0.30323922634124756
Norm Quadratic Average: 24.861812591552734
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6185415983200073
Linear Weight Rank: 10
Intra Cos: 0.9857441782951355
Inter Cos: 0.33734092116355896
Norm Quadratic Average: 15.841519355773926
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9869640469551086
Inter Cos: 0.42616599798202515
Norm Quadratic Average: 10.87250804901123
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.382793701171875
Accuracy: 0.5835
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.19858555495738983, Weights: 0.026330657303333282
NC2 Equiangle: Features: 0.34647129906548396, Weights: 0.1939111285739475
NC3 Self-Duality: 0.2533929944038391
NC4 NCC Mismatch: 0.129

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
Inter Cos: 0.09352367371320724
Norm Quadratic Average: 27.53066635131836
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02269267477095127
Inter Cos: 0.08776749670505524
Norm Quadratic Average: 20.27101707458496
Nearest Class Center Accuracy: 0.3515

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02597338892519474
Inter Cos: 0.07916811853647232
Norm Quadratic Average: 15.091903686523438
Nearest Class Center Accuracy: 0.3995

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02239220030605793
Inter Cos: 0.061130501329898834
Norm Quadratic Average: 16.12351417541504
Nearest Class Center Accuracy: 0.438

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02977965958416462
Inter Cos: 0.07211658358573914
Norm Quadratic Average: 10.229475021362305
Nearest Class Center Accuracy: 0.4575

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029519716277718544
Inter Cos: 0.0645354688167572
Norm Quadratic Average: 10.38950252532959
Nearest Class Center Accuracy: 0.5015

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04099603369832039
Inter Cos: 0.08247862756252289
Norm Quadratic Average: 6.1603617668151855
Nearest Class Center Accuracy: 0.5615

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08801913261413574
Inter Cos: 0.14214001595973969
Norm Quadratic Average: 3.771973133087158
Nearest Class Center Accuracy: 0.6295

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 24.00110626220703
Linear Weight Rank: 4031
Intra Cos: 0.20746226608753204
Inter Cos: 0.2667456269264221
Norm Quadratic Average: 36.34534454345703
Nearest Class Center Accuracy: 0.6085

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.79730224609375
Linear Weight Rank: 3669
Intra Cos: 0.24382071197032928
Inter Cos: 0.3299611210823059
Norm Quadratic Average: 19.15594482421875
Nearest Class Center Accuracy: 0.59

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6185415983200073
Linear Weight Rank: 10
Intra Cos: 0.2359078973531723
Inter Cos: 0.3709900379180908
Norm Quadratic Average: 12.277091026306152
Nearest Class Center Accuracy: 0.586

Output Layer:
Intra Cos: 0.22395218908786774
Inter Cos: 0.411513090133667
Norm Quadratic Average: 8.326631546020508
Nearest Class Center Accuracy: 0.5775

