Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_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: 0.11371058970689774
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: 0.026994381099939346
Inter Cos: 0.10196200013160706
Norm Quadratic Average: 20.56609344482422
Nearest Class Center Accuracy: 0.34175

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03150230646133423
Inter Cos: 0.09342707693576813
Norm Quadratic Average: 14.916791915893555
Nearest Class Center Accuracy: 0.3785

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028132880106568336
Inter Cos: 0.0748940035700798
Norm Quadratic Average: 16.143373489379883
Nearest Class Center Accuracy: 0.41525

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03630773723125458
Inter Cos: 0.0844755694270134
Norm Quadratic Average: 10.156340599060059
Nearest Class Center Accuracy: 0.454625

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0370185561478138
Inter Cos: 0.07604634761810303
Norm Quadratic Average: 10.384495735168457
Nearest Class Center Accuracy: 0.549375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08007379621267319
Inter Cos: 0.10082302242517471
Norm Quadratic Average: 6.239230632781982
Nearest Class Center Accuracy: 0.885625

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3679203987121582
Inter Cos: 0.16979992389678955
Norm Quadratic Average: 4.016721248626709
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 24.00184440612793
Linear Weight Rank: 4031
Intra Cos: 0.8843290209770203
Inter Cos: 0.31039828062057495
Norm Quadratic Average: 45.65122604370117
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.800480842590332
Linear Weight Rank: 3670
Intra Cos: 0.9773591160774231
Inter Cos: 0.32530736923217773
Norm Quadratic Average: 24.998554229736328
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.617375373840332
Linear Weight Rank: 10
Intra Cos: 0.9856530427932739
Inter Cos: 0.3475584089756012
Norm Quadratic Average: 15.862586975097656
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.987433671951294
Inter Cos: 0.39092764258384705
Norm Quadratic Average: 10.774256706237793
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.3378080368041991
Accuracy: 0.6005
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.18471036851406097, Weights: 0.021225564181804657
NC2 Equiangle: Features: 0.34885101318359374, Weights: 0.1961485120985243
NC3 Self-Duality: 0.250578910112381
NC4 NCC Mismatch: 0.12050000000000005

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: 0.024802355095744133
Inter Cos: 0.08953246474266052
Norm Quadratic Average: 20.563373565673828
Nearest Class Center Accuracy: 0.356

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03002038039267063
Inter Cos: 0.08623702079057693
Norm Quadratic Average: 14.915926933288574
Nearest Class Center Accuracy: 0.399

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02750389464199543
Inter Cos: 0.06630680710077286
Norm Quadratic Average: 16.155227661132812
Nearest Class Center Accuracy: 0.434

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.033258724957704544
Inter Cos: 0.07943203300237656
Norm Quadratic Average: 10.158527374267578
Nearest Class Center Accuracy: 0.4705

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03080456145107746
Inter Cos: 0.06491883099079132
Norm Quadratic Average: 10.374402046203613
Nearest Class Center Accuracy: 0.5155

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04292187839746475
Inter Cos: 0.08833081275224686
Norm Quadratic Average: 6.205234050750732
Nearest Class Center Accuracy: 0.571

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08656961470842361
Inter Cos: 0.14098793268203735
Norm Quadratic Average: 3.735785722732544
Nearest Class Center Accuracy: 0.6375

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 24.00184440612793
Linear Weight Rank: 4031
Intra Cos: 0.2196381390094757
Inter Cos: 0.2778831124305725
Norm Quadratic Average: 36.127403259277344
Nearest Class Center Accuracy: 0.6115

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.800480842590332
Linear Weight Rank: 3670
Intra Cos: 0.2670774459838867
Inter Cos: 0.32059383392333984
Norm Quadratic Average: 19.09649085998535
Nearest Class Center Accuracy: 0.5995

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.617375373840332
Linear Weight Rank: 10
Intra Cos: 0.268909752368927
Inter Cos: 0.3428916037082672
Norm Quadratic Average: 12.202402114868164
Nearest Class Center Accuracy: 0.5925

Output Layer:
Intra Cos: 0.2660500407218933
Inter Cos: 0.3733295202255249
Norm Quadratic Average: 8.22352409362793
Nearest Class Center Accuracy: 0.5845

