Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_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: 0.021450398489832878
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: 0.023161431774497032
Inter Cos: 0.07760816812515259
Norm Quadratic Average: 20.975908279418945
Nearest Class Center Accuracy: 0.345875

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02940463088452816
Inter Cos: 0.08171463757753372
Norm Quadratic Average: 15.641342163085938
Nearest Class Center Accuracy: 0.3735

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023982342332601547
Inter Cos: 0.06483939290046692
Norm Quadratic Average: 16.228479385375977
Nearest Class Center Accuracy: 0.413375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.035683486610651016
Inter Cos: 0.07959749549627304
Norm Quadratic Average: 10.360912322998047
Nearest Class Center Accuracy: 0.448125

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03772974759340286
Inter Cos: 0.07281895726919174
Norm Quadratic Average: 10.453408241271973
Nearest Class Center Accuracy: 0.535875

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07949678599834442
Inter Cos: 0.09731893986463547
Norm Quadratic Average: 6.183755874633789
Nearest Class Center Accuracy: 0.87525

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3785993754863739
Inter Cos: 0.18003860116004944
Norm Quadratic Average: 4.025608539581299
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 24.0025577545166
Linear Weight Rank: 4031
Intra Cos: 0.8900024890899658
Inter Cos: 0.28160345554351807
Norm Quadratic Average: 45.67710494995117
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.799284934997559
Linear Weight Rank: 3670
Intra Cos: 0.9782601594924927
Inter Cos: 0.2677476108074188
Norm Quadratic Average: 24.848249435424805
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.614135980606079
Linear Weight Rank: 10
Intra Cos: 0.9858261942863464
Inter Cos: 0.2912483811378479
Norm Quadratic Average: 15.650736808776855
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9888003468513489
Inter Cos: 0.4069599211215973
Norm Quadratic Average: 10.54990291595459
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.3103381271362304
Accuracy: 0.602
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.18606819212436676, Weights: 0.02152779884636402
NC2 Equiangle: Features: 0.35612831115722654, Weights: 0.1926790237426758
NC3 Self-Duality: 0.24901677668094635
NC4 NCC Mismatch: 0.136

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352367371320724
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: 0.022865163162350655
Inter Cos: 0.07060882449150085
Norm Quadratic Average: 20.918107986450195
Nearest Class Center Accuracy: 0.36

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029204821214079857
Inter Cos: 0.07909679412841797
Norm Quadratic Average: 15.597609519958496
Nearest Class Center Accuracy: 0.406

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023502632975578308
Inter Cos: 0.056426625698804855
Norm Quadratic Average: 16.19441032409668
Nearest Class Center Accuracy: 0.447

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03203568607568741
Inter Cos: 0.07846902310848236
Norm Quadratic Average: 10.342397689819336
Nearest Class Center Accuracy: 0.459

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030699195340275764
Inter Cos: 0.06355278939008713
Norm Quadratic Average: 10.436922073364258
Nearest Class Center Accuracy: 0.5025

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.040285442024469376
Inter Cos: 0.08698427677154541
Norm Quadratic Average: 6.152554035186768
Nearest Class Center Accuracy: 0.5735

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08672972768545151
Inter Cos: 0.14941199123859406
Norm Quadratic Average: 3.7608261108398438
Nearest Class Center Accuracy: 0.6355

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 24.0025577545166
Linear Weight Rank: 4031
Intra Cos: 0.22202837467193604
Inter Cos: 0.2726406753063202
Norm Quadratic Average: 36.572723388671875
Nearest Class Center Accuracy: 0.62

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.799284934997559
Linear Weight Rank: 3670
Intra Cos: 0.26894405484199524
Inter Cos: 0.35049617290496826
Norm Quadratic Average: 19.22092056274414
Nearest Class Center Accuracy: 0.6105

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.614135980606079
Linear Weight Rank: 10
Intra Cos: 0.2670086622238159
Inter Cos: 0.3826324939727783
Norm Quadratic Average: 12.1828031539917
Nearest Class Center Accuracy: 0.5985

Output Layer:
Intra Cos: 0.2627159655094147
Inter Cos: 0.41812941431999207
Norm Quadratic Average: 8.132603645324707
Nearest Class Center Accuracy: 0.5875

