Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_314159_weight_decay_0.007.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: 0.022580843418836594
Inter Cos: 0.1008775383234024
Norm Quadratic Average: 62.57051467895508
Nearest Class Center Accuracy: 0.323125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025332987308502197
Inter Cos: 0.0827089250087738
Norm Quadratic Average: 46.58736801147461
Nearest Class Center Accuracy: 0.359125

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02333519048988819
Inter Cos: 0.06861086934804916
Norm Quadratic Average: 49.29073715209961
Nearest Class Center Accuracy: 0.39225

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031183749437332153
Inter Cos: 0.07419311255216599
Norm Quadratic Average: 31.212270736694336
Nearest Class Center Accuracy: 0.420125

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032146453857421875
Inter Cos: 0.06448859721422195
Norm Quadratic Average: 31.92403221130371
Nearest Class Center Accuracy: 0.465625

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04571102187037468
Inter Cos: 0.0703660398721695
Norm Quadratic Average: 20.255659103393555
Nearest Class Center Accuracy: 0.5835

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07730186730623245
Inter Cos: 0.08141957223415375
Norm Quadratic Average: 14.433137893676758
Nearest Class Center Accuracy: 0.90875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.46125793457031
Linear Weight Rank: 4031
Intra Cos: 0.26633456349372864
Inter Cos: 0.1247560903429985
Norm Quadratic Average: 82.13253021240234
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.302526473999023
Linear Weight Rank: 3670
Intra Cos: 0.5910321474075317
Inter Cos: 0.2245047241449356
Norm Quadratic Average: 39.47633743286133
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.035036325454712
Linear Weight Rank: 10
Intra Cos: 0.7946708798408508
Inter Cos: 0.3204728662967682
Norm Quadratic Average: 25.962369918823242
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9009308218955994
Inter Cos: 0.44340792298316956
Norm Quadratic Average: 16.629430770874023
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.768262565612793
Accuracy: 0.5785
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.1931961178779602, Weights: 0.01574011705815792
NC2 Equiangle: Features: 0.41262164645724825, Weights: 0.0975529776679145
NC3 Self-Duality: 0.5390529632568359
NC4 NCC Mismatch: 0.13649999999999995

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: 0.02186773717403412
Inter Cos: 0.08790890872478485
Norm Quadratic Average: 62.37381362915039
Nearest Class Center Accuracy: 0.349

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02574774995446205
Inter Cos: 0.07763110101222992
Norm Quadratic Average: 46.414817810058594
Nearest Class Center Accuracy: 0.381

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02456413209438324
Inter Cos: 0.06009221822023392
Norm Quadratic Average: 49.179931640625
Nearest Class Center Accuracy: 0.416

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028411803767085075
Inter Cos: 0.06768748909235
Norm Quadratic Average: 31.118515014648438
Nearest Class Center Accuracy: 0.4455

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028385328128933907
Inter Cos: 0.05791610851883888
Norm Quadratic Average: 31.83814239501953
Nearest Class Center Accuracy: 0.477

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03261411562561989
Inter Cos: 0.06675166636705399
Norm Quadratic Average: 20.155139923095703
Nearest Class Center Accuracy: 0.493

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.037308067083358765
Inter Cos: 0.0760248601436615
Norm Quadratic Average: 14.275151252746582
Nearest Class Center Accuracy: 0.576

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.46125793457031
Linear Weight Rank: 4031
Intra Cos: 0.07674180716276169
Inter Cos: 0.13222721219062805
Norm Quadratic Average: 78.21052551269531
Nearest Class Center Accuracy: 0.6035

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.302526473999023
Linear Weight Rank: 3670
Intra Cos: 0.1602446287870407
Inter Cos: 0.2574109435081482
Norm Quadratic Average: 35.53588104248047
Nearest Class Center Accuracy: 0.583

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.035036325454712
Linear Weight Rank: 10
Intra Cos: 0.22710010409355164
Inter Cos: 0.36322519183158875
Norm Quadratic Average: 22.577564239501953
Nearest Class Center Accuracy: 0.5785

Output Layer:
Intra Cos: 0.2779543697834015
Inter Cos: 0.4731978178024292
Norm Quadratic Average: 14.192179679870605
Nearest Class Center Accuracy: 0.569

