Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_979323_test_samples_None_train_samples_None_weight_decay_0.01.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0198909230530262
Inter Cos: 0.10477276891469955
Norm Quadratic Average: 27.59718894958496
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01940876990556717
Inter Cos: 0.0712779238820076
Norm Quadratic Average: 4.402572154998779
Nearest Class Center Accuracy: 0.40654

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019982274621725082
Inter Cos: 0.05366969853639603
Norm Quadratic Average: 2.127891778945923
Nearest Class Center Accuracy: 0.53624

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01574893482029438
Inter Cos: 0.04581424966454506
Norm Quadratic Average: 1.4472665786743164
Nearest Class Center Accuracy: 0.62312

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025707880035042763
Inter Cos: 0.04057520255446434
Norm Quadratic Average: 0.9616499543190002
Nearest Class Center Accuracy: 0.77954

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06322389841079712
Inter Cos: 0.058116570115089417
Norm Quadratic Average: 0.660808265209198
Nearest Class Center Accuracy: 0.90364

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3521711528301239
Inter Cos: 0.1966833472251892
Norm Quadratic Average: 0.4533010721206665
Nearest Class Center Accuracy: 0.99516

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.8657991290092468
Inter Cos: 0.05667780339717865
Norm Quadratic Average: 0.7733927965164185
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.1491897106170654
Linear Weight Rank: 39
Intra Cos: 0.984413743019104
Inter Cos: 0.01736857369542122
Norm Quadratic Average: 23.771512985229492
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.154416084289551
Linear Weight Rank: 1340
Intra Cos: 0.9905943870544434
Inter Cos: 0.06769537925720215
Norm Quadratic Average: 15.993487358093262
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.1506707668304443
Linear Weight Rank: 9
Intra Cos: 0.9923639893531799
Inter Cos: 0.1075059249997139
Norm Quadratic Average: 10.954573631286621
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9935467839241028
Inter Cos: 0.20915217697620392
Norm Quadratic Average: 7.934671878814697
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.41640482754707336
Accuracy: 0.8747
NC1 Within Class Collapse: 2.8757073879241943
NC2 Equinorm: Features: 0.10578876733779907, Weights: 0.004778162110596895
NC2 Equiangle: Features: 0.11846434275309245, Weights: 0.033081889152526855
NC3 Self-Duality: 0.029769694432616234
NC4 NCC Mismatch: 0.011600000000000055

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526077270507812
Inter Cos: 0.1042705774307251
Norm Quadratic Average: 27.550140380859375
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018376439809799194
Inter Cos: 0.07353723049163818
Norm Quadratic Average: 4.400081157684326
Nearest Class Center Accuracy: 0.429

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01909779943525791
Inter Cos: 0.055293455719947815
Norm Quadratic Average: 2.1293063163757324
Nearest Class Center Accuracy: 0.5463

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.014827861450612545
Inter Cos: 0.046797048300504684
Norm Quadratic Average: 1.4496859312057495
Nearest Class Center Accuracy: 0.6261

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02185959368944168
Inter Cos: 0.04154197499155998
Norm Quadratic Average: 0.962174654006958
Nearest Class Center Accuracy: 0.7368

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04799361154437065
Inter Cos: 0.06163521111011505
Norm Quadratic Average: 0.656205952167511
Nearest Class Center Accuracy: 0.7975

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2514357268810272
Inter Cos: 0.21262270212173462
Norm Quadratic Average: 0.44072577357292175
Nearest Class Center Accuracy: 0.8492

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.4972493350505829
Inter Cos: 0.2232939600944519
Norm Quadratic Average: 0.7121533751487732
Nearest Class Center Accuracy: 0.872

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.1491897106170654
Linear Weight Rank: 39
Intra Cos: 0.6065994501113892
Inter Cos: 0.21621856093406677
Norm Quadratic Average: 21.163976669311523
Nearest Class Center Accuracy: 0.8721

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.154416084289551
Linear Weight Rank: 1340
Intra Cos: 0.6154189705848694
Inter Cos: 0.23803618550300598
Norm Quadratic Average: 14.229717254638672
Nearest Class Center Accuracy: 0.8723

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.1506707668304443
Linear Weight Rank: 9
Intra Cos: 0.6235866546630859
Inter Cos: 0.2663344144821167
Norm Quadratic Average: 9.747271537780762
Nearest Class Center Accuracy: 0.8734

Output Layer:
Intra Cos: 0.6406647562980652
Inter Cos: 0.3242381811141968
Norm Quadratic Average: 7.083470344543457
Nearest Class Center Accuracy: 0.8732

