Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_314159_weight_decay_0.005.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: 0.022797895595431328
Inter Cos: 0.10153081268072128
Norm Quadratic Average: 68.99469757080078
Nearest Class Center Accuracy: 0.326625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024549148976802826
Inter Cos: 0.084286630153656
Norm Quadratic Average: 51.243839263916016
Nearest Class Center Accuracy: 0.359125

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02342015691101551
Inter Cos: 0.06943749636411667
Norm Quadratic Average: 54.20777893066406
Nearest Class Center Accuracy: 0.392375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03151606768369675
Inter Cos: 0.07864551991224289
Norm Quadratic Average: 34.347251892089844
Nearest Class Center Accuracy: 0.42425

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03138573095202446
Inter Cos: 0.06720166653394699
Norm Quadratic Average: 35.103275299072266
Nearest Class Center Accuracy: 0.471375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04376720264554024
Inter Cos: 0.07077629864215851
Norm Quadratic Average: 22.406768798828125
Nearest Class Center Accuracy: 0.57775

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07040774077177048
Inter Cos: 0.0756489560008049
Norm Quadratic Average: 15.959745407104492
Nearest Class Center Accuracy: 0.89825

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 79.76185607910156
Linear Weight Rank: 4031
Intra Cos: 0.23503322899341583
Inter Cos: 0.11362183094024658
Norm Quadratic Average: 88.52408599853516
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 32.2492561340332
Linear Weight Rank: 3670
Intra Cos: 0.5374974012374878
Inter Cos: 0.21228273212909698
Norm Quadratic Average: 43.14488983154297
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.1432673931121826
Linear Weight Rank: 10
Intra Cos: 0.7630271911621094
Inter Cos: 0.3087974488735199
Norm Quadratic Average: 28.575273513793945
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9004838466644287
Inter Cos: 0.4602055549621582
Norm Quadratic Average: 18.581457138061523
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.9581966018676757
Accuracy: 0.5805
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20177818834781647, Weights: 0.015426439233124256
NC2 Equiangle: Features: 0.42560484144422744, Weights: 0.09516721301608616
NC3 Self-Duality: 0.5759032964706421
NC4 NCC Mismatch: 0.15600000000000003

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: 0.021969381719827652
Inter Cos: 0.08860711753368378
Norm Quadratic Average: 68.78086853027344
Nearest Class Center Accuracy: 0.351

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025077199563384056
Inter Cos: 0.07479699701070786
Norm Quadratic Average: 51.04138946533203
Nearest Class Center Accuracy: 0.382

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024633513763546944
Inter Cos: 0.06070940941572189
Norm Quadratic Average: 54.09538650512695
Nearest Class Center Accuracy: 0.418

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028668580576777458
Inter Cos: 0.0692424401640892
Norm Quadratic Average: 34.24098205566406
Nearest Class Center Accuracy: 0.4525

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02757568471133709
Inter Cos: 0.058171842247247696
Norm Quadratic Average: 35.00273132324219
Nearest Class Center Accuracy: 0.4825

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030218152329325676
Inter Cos: 0.06466829031705856
Norm Quadratic Average: 22.29508399963379
Nearest Class Center Accuracy: 0.4995

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034124501049518585
Inter Cos: 0.07184207439422607
Norm Quadratic Average: 15.787232398986816
Nearest Class Center Accuracy: 0.5745

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 79.76185607910156
Linear Weight Rank: 4031
Intra Cos: 0.06267159432172775
Inter Cos: 0.1219569742679596
Norm Quadratic Average: 84.5303955078125
Nearest Class Center Accuracy: 0.6095

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 32.2492561340332
Linear Weight Rank: 3670
Intra Cos: 0.13342149555683136
Inter Cos: 0.24090704321861267
Norm Quadratic Average: 39.00579071044922
Nearest Class Center Accuracy: 0.5885

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.1432673931121826
Linear Weight Rank: 10
Intra Cos: 0.19653713703155518
Inter Cos: 0.35018661618232727
Norm Quadratic Average: 24.89381217956543
Nearest Class Center Accuracy: 0.578

Output Layer:
Intra Cos: 0.2561292052268982
Inter Cos: 0.47470471262931824
Norm Quadratic Average: 15.826542854309082
Nearest Class Center Accuracy: 0.559

