Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_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: 0.11371058225631714
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: 0.023468125611543655
Inter Cos: 0.09935401380062103
Norm Quadratic Average: 68.10607147216797
Nearest Class Center Accuracy: 0.335125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02568468637764454
Inter Cos: 0.09097867459058762
Norm Quadratic Average: 51.083316802978516
Nearest Class Center Accuracy: 0.37275

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02201746590435505
Inter Cos: 0.0687638372182846
Norm Quadratic Average: 54.35784149169922
Nearest Class Center Accuracy: 0.403125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030943404883146286
Inter Cos: 0.07844001799821854
Norm Quadratic Average: 34.93712615966797
Nearest Class Center Accuracy: 0.4195

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029273606836795807
Inter Cos: 0.06499110907316208
Norm Quadratic Average: 35.48470687866211
Nearest Class Center Accuracy: 0.467

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04098167270421982
Inter Cos: 0.073203444480896
Norm Quadratic Average: 22.647165298461914
Nearest Class Center Accuracy: 0.584

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07038155198097229
Inter Cos: 0.07785572856664658
Norm Quadratic Average: 16.012439727783203
Nearest Class Center Accuracy: 0.8945

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 79.76371765136719
Linear Weight Rank: 4031
Intra Cos: 0.22633984684944153
Inter Cos: 0.11601226776838303
Norm Quadratic Average: 88.09515380859375
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 32.24485778808594
Linear Weight Rank: 3670
Intra Cos: 0.5142718553543091
Inter Cos: 0.21934166550636292
Norm Quadratic Average: 42.866756439208984
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.135453462600708
Linear Weight Rank: 10
Intra Cos: 0.7399742007255554
Inter Cos: 0.3189559578895569
Norm Quadratic Average: 28.589284896850586
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.887570858001709
Inter Cos: 0.4726000130176544
Norm Quadratic Average: 18.581737518310547
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.977941307067871
Accuracy: 0.575
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2179587483406067, Weights: 0.012515674345195293
NC2 Equiangle: Features: 0.43222550286187067, Weights: 0.09523972405327691
NC3 Self-Duality: 0.5859233140945435
NC4 NCC Mismatch: 0.133

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: 0.022722136229276657
Inter Cos: 0.0856294333934784
Norm Quadratic Average: 67.71231842041016
Nearest Class Center Accuracy: 0.3535

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02563556842505932
Inter Cos: 0.078915536403656
Norm Quadratic Average: 50.80624008178711
Nearest Class Center Accuracy: 0.4005

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02185646817088127
Inter Cos: 0.05955706164240837
Norm Quadratic Average: 54.16305923461914
Nearest Class Center Accuracy: 0.4405

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028765005990862846
Inter Cos: 0.07099476456642151
Norm Quadratic Average: 34.81052780151367
Nearest Class Center Accuracy: 0.4435

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026268059387803078
Inter Cos: 0.05963738635182381
Norm Quadratic Average: 35.39992904663086
Nearest Class Center Accuracy: 0.4795

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030115699395537376
Inter Cos: 0.07047718018293381
Norm Quadratic Average: 22.563629150390625
Nearest Class Center Accuracy: 0.5065

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0350906178355217
Inter Cos: 0.06664954870939255
Norm Quadratic Average: 15.880434036254883
Nearest Class Center Accuracy: 0.5695

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 79.76371765136719
Linear Weight Rank: 4031
Intra Cos: 0.06511566787958145
Inter Cos: 0.11769113689661026
Norm Quadratic Average: 84.36812591552734
Nearest Class Center Accuracy: 0.604

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 32.24485778808594
Linear Weight Rank: 3670
Intra Cos: 0.13680388033390045
Inter Cos: 0.23584020137786865
Norm Quadratic Average: 38.9529914855957
Nearest Class Center Accuracy: 0.578

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.135453462600708
Linear Weight Rank: 10
Intra Cos: 0.1995098888874054
Inter Cos: 0.35172146558761597
Norm Quadratic Average: 25.09538459777832
Nearest Class Center Accuracy: 0.567

Output Layer:
Intra Cos: 0.2501514256000519
Inter Cos: 0.48489755392074585
Norm Quadratic Average: 15.96013355255127
Nearest Class Center Accuracy: 0.552

