Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_weight_decay_0.003.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: 0.02391357719898224
Inter Cos: 0.09662123769521713
Norm Quadratic Average: 34.741455078125
Nearest Class Center Accuracy: 0.299625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029212163761258125
Inter Cos: 0.10470351576805115
Norm Quadratic Average: 27.95108985900879
Nearest Class Center Accuracy: 0.3575

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034707456827163696
Inter Cos: 0.10812532156705856
Norm Quadratic Average: 32.57276916503906
Nearest Class Center Accuracy: 0.40325

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05118430405855179
Inter Cos: 0.1363498568534851
Norm Quadratic Average: 20.15911865234375
Nearest Class Center Accuracy: 0.431875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05829451605677605
Inter Cos: 0.14057250320911407
Norm Quadratic Average: 17.03799819946289
Nearest Class Center Accuracy: 0.45675

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07384516298770905
Inter Cos: 0.14655548334121704
Norm Quadratic Average: 8.568624496459961
Nearest Class Center Accuracy: 0.507125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1038348376750946
Inter Cos: 0.16181723773479462
Norm Quadratic Average: 5.925423622131348
Nearest Class Center Accuracy: 0.6665

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 87.82142639160156
Linear Weight Rank: 4031
Intra Cos: 0.3077305853366852
Inter Cos: 0.27859023213386536
Norm Quadratic Average: 22.9459285736084
Nearest Class Center Accuracy: 0.960375

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 35.551212310791016
Linear Weight Rank: 3670
Intra Cos: 0.5947164297103882
Inter Cos: 0.435920387506485
Norm Quadratic Average: 20.234027862548828
Nearest Class Center Accuracy: 0.99825

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.1142420768737793
Linear Weight Rank: 10
Intra Cos: 0.7275562882423401
Inter Cos: 0.5449294447898865
Norm Quadratic Average: 23.738807678222656
Nearest Class Center Accuracy: 0.999375

Output Layer:
Intra Cos: 0.8239680528640747
Inter Cos: 0.704257607460022
Norm Quadratic Average: 28.921295166015625
Nearest Class Center Accuracy: 0.99925

Test Set:
Average Loss: 2.560124946594238
Accuracy: 0.589
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.23744697868824005, Weights: 0.050001416355371475
NC2 Equiangle: Features: 0.44266590542263456, Weights: 0.17172075907389323
NC3 Self-Duality: 0.4286384582519531
NC4 NCC Mismatch: 0.14900000000000002

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: 0.02504565380513668
Inter Cos: 0.07974033057689667
Norm Quadratic Average: 34.48290252685547
Nearest Class Center Accuracy: 0.313

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03241534158587456
Inter Cos: 0.08988569676876068
Norm Quadratic Average: 27.783029556274414
Nearest Class Center Accuracy: 0.369

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036325808614492416
Inter Cos: 0.09541857242584229
Norm Quadratic Average: 32.4393424987793
Nearest Class Center Accuracy: 0.4235

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05027054250240326
Inter Cos: 0.12042654305696487
Norm Quadratic Average: 20.106060028076172
Nearest Class Center Accuracy: 0.453

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05562455952167511
Inter Cos: 0.1235203891992569
Norm Quadratic Average: 17.03362464904785
Nearest Class Center Accuracy: 0.4655

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06335972249507904
Inter Cos: 0.1351577341556549
Norm Quadratic Average: 8.55724811553955
Nearest Class Center Accuracy: 0.485

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07464282214641571
Inter Cos: 0.14148880541324615
Norm Quadratic Average: 5.890300750732422
Nearest Class Center Accuracy: 0.5105

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 87.82142639160156
Linear Weight Rank: 4031
Intra Cos: 0.1500416398048401
Inter Cos: 0.25339117646217346
Norm Quadratic Average: 22.165555953979492
Nearest Class Center Accuracy: 0.5675

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 35.551212310791016
Linear Weight Rank: 3670
Intra Cos: 0.24211448431015015
Inter Cos: 0.3790380656719208
Norm Quadratic Average: 18.97978973388672
Nearest Class Center Accuracy: 0.5825

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.1142420768737793
Linear Weight Rank: 10
Intra Cos: 0.2749233543872833
Inter Cos: 0.45660683512687683
Norm Quadratic Average: 22.103609085083008
Nearest Class Center Accuracy: 0.571

Output Layer:
Intra Cos: 0.3122069835662842
Inter Cos: 0.5633839964866638
Norm Quadratic Average: 26.787519454956055
Nearest Class Center Accuracy: 0.549

