Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_314159_weight_decay_0.0005.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: 0.025035379454493523
Inter Cos: 0.09468822181224823
Norm Quadratic Average: 33.811336517333984
Nearest Class Center Accuracy: 0.300875

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03207970783114433
Inter Cos: 0.10870666801929474
Norm Quadratic Average: 26.820526123046875
Nearest Class Center Accuracy: 0.354625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0361316092312336
Inter Cos: 0.10401398688554764
Norm Quadratic Average: 31.291728973388672
Nearest Class Center Accuracy: 0.41025

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05237128585577011
Inter Cos: 0.13205640017986298
Norm Quadratic Average: 19.741657257080078
Nearest Class Center Accuracy: 0.436625

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06591075658798218
Inter Cos: 0.1391480267047882
Norm Quadratic Average: 18.24005699157715
Nearest Class Center Accuracy: 0.469625

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08808540552854538
Inter Cos: 0.1637905240058899
Norm Quadratic Average: 10.044150352478027
Nearest Class Center Accuracy: 0.511375

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.11784430593252182
Inter Cos: 0.16954319179058075
Norm Quadratic Average: 7.375442028045654
Nearest Class Center Accuracy: 0.678

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.00111389160156
Linear Weight Rank: 4031
Intra Cos: 0.3221266269683838
Inter Cos: 0.2704186737537384
Norm Quadratic Average: 29.426071166992188
Nearest Class Center Accuracy: 0.95925

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.06455612182617
Linear Weight Rank: 3670
Intra Cos: 0.6165931224822998
Inter Cos: 0.4303210377693176
Norm Quadratic Average: 25.427934646606445
Nearest Class Center Accuracy: 0.99825

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.252506971359253
Linear Weight Rank: 10
Intra Cos: 0.7555724382400513
Inter Cos: 0.5422003865242004
Norm Quadratic Average: 29.916101455688477
Nearest Class Center Accuracy: 0.9995

Output Layer:
Intra Cos: 0.8541718125343323
Inter Cos: 0.7073057889938354
Norm Quadratic Average: 36.72378158569336
Nearest Class Center Accuracy: 0.99925

Test Set:
Average Loss: 3.2429676361083986
Accuracy: 0.59
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.25079745054244995, Weights: 0.044299352914094925
NC2 Equiangle: Features: 0.42288292778862846, Weights: 0.165961668226454
NC3 Self-Duality: 0.4535882771015167
NC4 NCC Mismatch: 0.14849999999999997

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: 0.025282172486186028
Inter Cos: 0.08923119306564331
Norm Quadratic Average: 33.6357536315918
Nearest Class Center Accuracy: 0.318

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03442877158522606
Inter Cos: 0.10517232120037079
Norm Quadratic Average: 26.70193862915039
Nearest Class Center Accuracy: 0.3745

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03704817593097687
Inter Cos: 0.09317599982023239
Norm Quadratic Average: 31.167516708374023
Nearest Class Center Accuracy: 0.433

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05112892761826515
Inter Cos: 0.11899721622467041
Norm Quadratic Average: 19.681434631347656
Nearest Class Center Accuracy: 0.4545

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06248123571276665
Inter Cos: 0.12468423694372177
Norm Quadratic Average: 18.21830177307129
Nearest Class Center Accuracy: 0.4745

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07387567311525345
Inter Cos: 0.1438474804162979
Norm Quadratic Average: 10.02366828918457
Nearest Class Center Accuracy: 0.4745

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0825885534286499
Inter Cos: 0.14448128640651703
Norm Quadratic Average: 7.327292442321777
Nearest Class Center Accuracy: 0.5145

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.00111389160156
Linear Weight Rank: 4031
Intra Cos: 0.14003849029541016
Inter Cos: 0.23519428074359894
Norm Quadratic Average: 28.371543884277344
Nearest Class Center Accuracy: 0.5785

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.06455612182617
Linear Weight Rank: 3670
Intra Cos: 0.22699731588363647
Inter Cos: 0.3566383719444275
Norm Quadratic Average: 23.78658676147461
Nearest Class Center Accuracy: 0.5955

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.252506971359253
Linear Weight Rank: 10
Intra Cos: 0.2663481533527374
Inter Cos: 0.4424629509449005
Norm Quadratic Average: 27.717283248901367
Nearest Class Center Accuracy: 0.579

Output Layer:
Intra Cos: 0.30227378010749817
Inter Cos: 0.5568680763244629
Norm Quadratic Average: 33.809322357177734
Nearest Class Center Accuracy: 0.557

