Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_weight_decay_0.001.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: 0.023544814437627792
Inter Cos: 0.09920090436935425
Norm Quadratic Average: 82.37553405761719
Nearest Class Center Accuracy: 0.332625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02636602707207203
Inter Cos: 0.08847017586231232
Norm Quadratic Average: 62.05173110961914
Nearest Class Center Accuracy: 0.3715

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023579265922307968
Inter Cos: 0.07064619660377502
Norm Quadratic Average: 66.02131652832031
Nearest Class Center Accuracy: 0.401625

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03315224498510361
Inter Cos: 0.08116794377565384
Norm Quadratic Average: 42.182640075683594
Nearest Class Center Accuracy: 0.41725

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03185608610510826
Inter Cos: 0.07045204937458038
Norm Quadratic Average: 43.00379943847656
Nearest Class Center Accuracy: 0.460375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04326004907488823
Inter Cos: 0.0758594200015068
Norm Quadratic Average: 27.557371139526367
Nearest Class Center Accuracy: 0.558125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06306712329387665
Inter Cos: 0.07644432783126831
Norm Quadratic Average: 19.514379501342773
Nearest Class Center Accuracy: 0.846125

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.6382827758789
Linear Weight Rank: 4031
Intra Cos: 0.18600404262542725
Inter Cos: 0.10312540829181671
Norm Quadratic Average: 104.01026153564453
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.05854797363281
Linear Weight Rank: 3670
Intra Cos: 0.4301561713218689
Inter Cos: 0.1955384910106659
Norm Quadratic Average: 53.55173110961914
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.4405264854431152
Linear Weight Rank: 10
Intra Cos: 0.6594530344009399
Inter Cos: 0.31314730644226074
Norm Quadratic Average: 37.3553352355957
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8707947731018066
Inter Cos: 0.5250549912452698
Norm Quadratic Average: 25.659332275390625
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.5541442794799805
Accuracy: 0.5925
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.21628724038600922, Weights: 0.013000212609767914
NC2 Equiangle: Features: 0.43034837510850693, Weights: 0.09246756235758463
NC3 Self-Duality: 0.6341358423233032
NC4 NCC Mismatch: 0.14249999999999996

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: 0.022770095616579056
Inter Cos: 0.08539587259292603
Norm Quadratic Average: 81.90779876708984
Nearest Class Center Accuracy: 0.3535

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026526937261223793
Inter Cos: 0.07687460631132126
Norm Quadratic Average: 61.71818542480469
Nearest Class Center Accuracy: 0.407

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023688577115535736
Inter Cos: 0.06172630935907364
Norm Quadratic Average: 65.785400390625
Nearest Class Center Accuracy: 0.4375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030713336542248726
Inter Cos: 0.07129735499620438
Norm Quadratic Average: 42.049041748046875
Nearest Class Center Accuracy: 0.447

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02859402261674404
Inter Cos: 0.06068040803074837
Norm Quadratic Average: 42.90888595581055
Nearest Class Center Accuracy: 0.4775

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031919822096824646
Inter Cos: 0.07329397648572922
Norm Quadratic Average: 27.456117630004883
Nearest Class Center Accuracy: 0.5015

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03292220085859299
Inter Cos: 0.06504964828491211
Norm Quadratic Average: 19.361576080322266
Nearest Class Center Accuracy: 0.5655

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.6382827758789
Linear Weight Rank: 4031
Intra Cos: 0.05746934190392494
Inter Cos: 0.10318459570407867
Norm Quadratic Average: 100.22929382324219
Nearest Class Center Accuracy: 0.6065

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.05854797363281
Linear Weight Rank: 3670
Intra Cos: 0.11938108503818512
Inter Cos: 0.20321349799633026
Norm Quadratic Average: 49.367496490478516
Nearest Class Center Accuracy: 0.5755

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.4405264854431152
Linear Weight Rank: 10
Intra Cos: 0.18618713319301605
Inter Cos: 0.3208698630332947
Norm Quadratic Average: 33.23781204223633
Nearest Class Center Accuracy: 0.57

Output Layer:
Intra Cos: 0.2677505612373352
Inter Cos: 0.49418699741363525
Norm Quadratic Average: 22.18606185913086
Nearest Class Center Accuracy: 0.5645

