Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_314159_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: 0.022553041577339172
Inter Cos: 0.10074129700660706
Norm Quadratic Average: 20.71601676940918
Nearest Class Center Accuracy: 0.327125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025055307894945145
Inter Cos: 0.0846688449382782
Norm Quadratic Average: 15.31330394744873
Nearest Class Center Accuracy: 0.363375

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023905200883746147
Inter Cos: 0.07109600305557251
Norm Quadratic Average: 16.138227462768555
Nearest Class Center Accuracy: 0.40425

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031143393367528915
Inter Cos: 0.08199365437030792
Norm Quadratic Average: 10.10028076171875
Nearest Class Center Accuracy: 0.43925

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03546025976538658
Inter Cos: 0.07521996647119522
Norm Quadratic Average: 10.305333137512207
Nearest Class Center Accuracy: 0.53

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0769452154636383
Inter Cos: 0.09636580944061279
Norm Quadratic Average: 6.097817420959473
Nearest Class Center Accuracy: 0.872125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.37151941657066345
Inter Cos: 0.1753697395324707
Norm Quadratic Average: 3.980052947998047
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.99931526184082
Linear Weight Rank: 4031
Intra Cos: 0.8851337432861328
Inter Cos: 0.31005576252937317
Norm Quadratic Average: 45.10723114013672
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.795608520507812
Linear Weight Rank: 3669
Intra Cos: 0.9795845746994019
Inter Cos: 0.2983713150024414
Norm Quadratic Average: 25.09039878845215
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6010878086090088
Linear Weight Rank: 10
Intra Cos: 0.986167848110199
Inter Cos: 0.3172638714313507
Norm Quadratic Average: 16.123071670532227
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.987790048122406
Inter Cos: 0.45894792675971985
Norm Quadratic Average: 11.151121139526367
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.3756630401611327
Accuracy: 0.586
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.1913238912820816, Weights: 0.027954187244176865
NC2 Equiangle: Features: 0.3401274151272244, Weights: 0.21294360690646702
NC3 Self-Duality: 0.22538024187088013
NC4 NCC Mismatch: 0.10650000000000004

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: 0.02173309586942196
Inter Cos: 0.08795306831598282
Norm Quadratic Average: 20.64914894104004
Nearest Class Center Accuracy: 0.3515

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025492684915661812
Inter Cos: 0.07525651156902313
Norm Quadratic Average: 15.256926536560059
Nearest Class Center Accuracy: 0.383

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02408953197300434
Inter Cos: 0.062458306550979614
Norm Quadratic Average: 16.10207748413086
Nearest Class Center Accuracy: 0.427

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027777818962931633
Inter Cos: 0.07202031463384628
Norm Quadratic Average: 10.074345588684082
Nearest Class Center Accuracy: 0.4565

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02886180765926838
Inter Cos: 0.0645340085029602
Norm Quadratic Average: 10.282562255859375
Nearest Class Center Accuracy: 0.499

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03820359334349632
Inter Cos: 0.07845430076122284
Norm Quadratic Average: 6.065283298492432
Nearest Class Center Accuracy: 0.5675

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08147240430116653
Inter Cos: 0.14535468816757202
Norm Quadratic Average: 3.7195475101470947
Nearest Class Center Accuracy: 0.6195

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.99931526184082
Linear Weight Rank: 4031
Intra Cos: 0.1959465742111206
Inter Cos: 0.2718043327331543
Norm Quadratic Average: 36.24474334716797
Nearest Class Center Accuracy: 0.6005

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.795608520507812
Linear Weight Rank: 3669
Intra Cos: 0.22430123388767242
Inter Cos: 0.3214719593524933
Norm Quadratic Average: 19.40723419189453
Nearest Class Center Accuracy: 0.5945

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6010878086090088
Linear Weight Rank: 10
Intra Cos: 0.21606670320034027
Inter Cos: 0.34265655279159546
Norm Quadratic Average: 12.524434089660645
Nearest Class Center Accuracy: 0.591

Output Layer:
Intra Cos: 0.20424266159534454
Inter Cos: 0.3707396984100342
Norm Quadratic Average: 8.551405906677246
Nearest Class Center Accuracy: 0.5755

