Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_314159_test_samples_None_train_samples_None_weight_decay_0.0001.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01989092119038105
Inter Cos: 0.10477276146411896
Norm Quadratic Average: 27.59718132019043
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.020484259352087975
Inter Cos: 0.0733414888381958
Norm Quadratic Average: 32.74570083618164
Nearest Class Center Accuracy: 0.3919

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02506595477461815
Inter Cos: 0.06352261453866959
Norm Quadratic Average: 30.98896598815918
Nearest Class Center Accuracy: 0.5158

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023697499185800552
Inter Cos: 0.05223941057920456
Norm Quadratic Average: 37.41926956176758
Nearest Class Center Accuracy: 0.5901

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03049677424132824
Inter Cos: 0.04450071230530739
Norm Quadratic Average: 20.265037536621094
Nearest Class Center Accuracy: 0.69736

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.042605165392160416
Inter Cos: 0.045366570353507996
Norm Quadratic Average: 14.460801124572754
Nearest Class Center Accuracy: 0.7653

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12299066036939621
Inter Cos: 0.08961263298988342
Norm Quadratic Average: 6.178737163543701
Nearest Class Center Accuracy: 0.8805

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.4181632101535797
Inter Cos: 0.14000698924064636
Norm Quadratic Average: 4.156714916229248
Nearest Class Center Accuracy: 0.97832

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 73.46746063232422
Linear Weight Rank: 4031
Intra Cos: 0.841951310634613
Inter Cos: 0.1257915198802948
Norm Quadratic Average: 24.026906967163086
Nearest Class Center Accuracy: 0.99086

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.99310302734375
Linear Weight Rank: 3669
Intra Cos: 0.904439389705658
Inter Cos: 0.06183294951915741
Norm Quadratic Average: 21.840152740478516
Nearest Class Center Accuracy: 0.996

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 4.11626672744751
Linear Weight Rank: 10
Intra Cos: 0.9055653214454651
Inter Cos: 0.06473639607429504
Norm Quadratic Average: 21.607421875
Nearest Class Center Accuracy: 0.99878

Output Layer:
Intra Cos: 0.9682514071464539
Inter Cos: 0.3502567410469055
Norm Quadratic Average: 25.277982711791992
Nearest Class Center Accuracy: 0.99996

Test Set:
Average Loss: 1.3046983633041382
Accuracy: 0.8046
NC1 Within Class Collapse: 6.655738353729248
NC2 Equinorm: Features: 0.2710818946361542, Weights: 0.013135622255504131
NC2 Equiangle: Features: 0.1514648331536187, Weights: 0.11906952328152126
NC3 Self-Duality: 0.4070079028606415
NC4 NCC Mismatch: 0.09509999999999996

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526073545217514
Inter Cos: 0.1042705774307251
Norm Quadratic Average: 27.550134658813477
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019228938966989517
Inter Cos: 0.07399750500917435
Norm Quadratic Average: 32.72480392456055
Nearest Class Center Accuracy: 0.4046

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023625824600458145
Inter Cos: 0.06424105167388916
Norm Quadratic Average: 30.998703002929688
Nearest Class Center Accuracy: 0.5211

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021693097427487373
Inter Cos: 0.052807100117206573
Norm Quadratic Average: 37.45399475097656
Nearest Class Center Accuracy: 0.5959

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02684161625802517
Inter Cos: 0.0456153079867363
Norm Quadratic Average: 20.2763614654541
Nearest Class Center Accuracy: 0.6728

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03666757047176361
Inter Cos: 0.04694252833724022
Norm Quadratic Average: 14.418792724609375
Nearest Class Center Accuracy: 0.7053

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09664634615182877
Inter Cos: 0.09560410678386688
Norm Quadratic Average: 6.100586891174316
Nearest Class Center Accuracy: 0.7307

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.24216704070568085
Inter Cos: 0.18651670217514038
Norm Quadratic Average: 4.0074944496154785
Nearest Class Center Accuracy: 0.7699

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 73.46746063232422
Linear Weight Rank: 4031
Intra Cos: 0.4800741970539093
Inter Cos: 0.2888839840888977
Norm Quadratic Average: 22.3480281829834
Nearest Class Center Accuracy: 0.7664

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.99310302734375
Linear Weight Rank: 3669
Intra Cos: 0.5085507035255432
Inter Cos: 0.2679755389690399
Norm Quadratic Average: 20.14759635925293
Nearest Class Center Accuracy: 0.7681

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 4.11626672744751
Linear Weight Rank: 10
Intra Cos: 0.5129560232162476
Inter Cos: 0.28074854612350464
Norm Quadratic Average: 20.010740280151367
Nearest Class Center Accuracy: 0.7741

Output Layer:
Intra Cos: 0.5705217123031616
Inter Cos: 0.41351118683815
Norm Quadratic Average: 23.078657150268555
Nearest Class Center Accuracy: 0.7918

