Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_979323_test_samples_None_train_samples_None_weight_decay_0.02.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0198909230530262
Inter Cos: 0.10477276891469955
Norm Quadratic Average: 27.59718894958496
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019816135987639427
Inter Cos: 0.07407812029123306
Norm Quadratic Average: 3.142611265182495
Nearest Class Center Accuracy: 0.4048

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02171354368329048
Inter Cos: 0.05735095962882042
Norm Quadratic Average: 1.5849913358688354
Nearest Class Center Accuracy: 0.53312

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0177314393222332
Inter Cos: 0.045747075229883194
Norm Quadratic Average: 1.12825345993042
Nearest Class Center Accuracy: 0.6255

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03125516325235367
Inter Cos: 0.051016923040151596
Norm Quadratic Average: 0.7849180102348328
Nearest Class Center Accuracy: 0.77646

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.060233213007450104
Inter Cos: 0.06601732969284058
Norm Quadratic Average: 0.6576891541481018
Nearest Class Center Accuracy: 0.88942

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.28199079632759094
Inter Cos: 0.21267777681350708
Norm Quadratic Average: 0.4184112250804901
Nearest Class Center Accuracy: 0.98838

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.8348970413208008
Inter Cos: 0.24350810050964355
Norm Quadratic Average: 0.613639771938324
Nearest Class Center Accuracy: 0.99996

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.0447311401367188
Linear Weight Rank: 10
Intra Cos: 0.9816009402275085
Inter Cos: 0.20461159944534302
Norm Quadratic Average: 22.688072204589844
Nearest Class Center Accuracy: 0.99998

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.047210216522217
Linear Weight Rank: 1476
Intra Cos: 0.9885496497154236
Inter Cos: 0.2067258059978485
Norm Quadratic Average: 15.258994102478027
Nearest Class Center Accuracy: 0.99998

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.0469377040863037
Linear Weight Rank: 9
Intra Cos: 0.990989089012146
Inter Cos: 0.19112929701805115
Norm Quadratic Average: 10.49239444732666
Nearest Class Center Accuracy: 0.99998

Output Layer:
Intra Cos: 0.9933019280433655
Inter Cos: 0.16609445214271545
Norm Quadratic Average: 7.670926094055176
Nearest Class Center Accuracy: 0.99998

Test Set:
Average Loss: 0.44105028219223025
Accuracy: 0.8625
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.10970759391784668, Weights: 0.004281068220734596
NC2 Equiangle: Features: 0.1522875467936198, Weights: 0.0982434802585178
NC3 Self-Duality: 0.05260509252548218
NC4 NCC Mismatch: 0.011900000000000022

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526077270507812
Inter Cos: 0.1042705774307251
Norm Quadratic Average: 27.550140380859375
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018563728779554367
Inter Cos: 0.07537755370140076
Norm Quadratic Average: 3.140631675720215
Nearest Class Center Accuracy: 0.422

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.020514721050858498
Inter Cos: 0.05856209993362427
Norm Quadratic Average: 1.5858256816864014
Nearest Class Center Accuracy: 0.5416

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01667151041328907
Inter Cos: 0.0466095432639122
Norm Quadratic Average: 1.1298067569732666
Nearest Class Center Accuracy: 0.6311

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027002500370144844
Inter Cos: 0.05219799652695656
Norm Quadratic Average: 0.7850325107574463
Nearest Class Center Accuracy: 0.7333

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.046252164989709854
Inter Cos: 0.06967822462320328
Norm Quadratic Average: 0.6542259454727173
Nearest Class Center Accuracy: 0.7898

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.20561085641384125
Inter Cos: 0.21991410851478577
Norm Quadratic Average: 0.4099515676498413
Nearest Class Center Accuracy: 0.8347

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.4753562808036804
Inter Cos: 0.2945464551448822
Norm Quadratic Average: 0.5676197409629822
Nearest Class Center Accuracy: 0.8615

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.0447311401367188
Linear Weight Rank: 10
Intra Cos: 0.5815109610557556
Inter Cos: 0.3265138566493988
Norm Quadratic Average: 20.2457332611084
Nearest Class Center Accuracy: 0.864

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.047210216522217
Linear Weight Rank: 1476
Intra Cos: 0.5959253907203674
Inter Cos: 0.3363637626171112
Norm Quadratic Average: 13.61669635772705
Nearest Class Center Accuracy: 0.8645

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.0469377040863037
Linear Weight Rank: 9
Intra Cos: 0.6047226786613464
Inter Cos: 0.3344009220600128
Norm Quadratic Average: 9.356624603271484
Nearest Class Center Accuracy: 0.8636

Output Layer:
Intra Cos: 0.6292429566383362
Inter Cos: 0.3177494406700134
Norm Quadratic Average: 6.853372573852539
Nearest Class Center Accuracy: 0.8623

