Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_314159_test_samples_None_train_samples_None_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: 0.01989092119038105
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: 0.019765883684158325
Inter Cos: 0.07296241074800491
Norm Quadratic Average: 3.340834617614746
Nearest Class Center Accuracy: 0.40444

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.020365426316857338
Inter Cos: 0.05683834105730057
Norm Quadratic Average: 1.6633158922195435
Nearest Class Center Accuracy: 0.53968

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01668708771467209
Inter Cos: 0.044890403747558594
Norm Quadratic Average: 1.287974238395691
Nearest Class Center Accuracy: 0.62342

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024613529443740845
Inter Cos: 0.04347439482808113
Norm Quadratic Average: 0.8694969415664673
Nearest Class Center Accuracy: 0.76338

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05749136209487915
Inter Cos: 0.07341707497835159
Norm Quadratic Average: 0.6157028079032898
Nearest Class Center Accuracy: 0.90046

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3702453076839447
Inter Cos: 0.24911686778068542
Norm Quadratic Average: 0.4398716986179352
Nearest Class Center Accuracy: 0.99802

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.8811790347099304
Inter Cos: 0.06059880182147026
Norm Quadratic Average: 0.745608925819397
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.209257125854492
Linear Weight Rank: 166
Intra Cos: 0.9843750596046448
Inter Cos: 0.018912706524133682
Norm Quadratic Average: 23.653966903686523
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.2224159240722656
Linear Weight Rank: 1030
Intra Cos: 0.9907588958740234
Inter Cos: 0.04681793972849846
Norm Quadratic Average: 16.288541793823242
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.2085769176483154
Linear Weight Rank: 9
Intra Cos: 0.9926357865333557
Inter Cos: 0.06939244270324707
Norm Quadratic Average: 11.479209899902344
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9936943650245667
Inter Cos: 0.0847637951374054
Norm Quadratic Average: 8.449222564697266
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.39698968734741213
Accuracy: 0.8818
NC1 Within Class Collapse: 2.914296865463257
NC2 Equinorm: Features: 0.11999829858541489, Weights: 0.0034700145479291677
NC2 Equiangle: Features: 0.12125423219468859, Weights: 0.01389625867207845
NC3 Self-Duality: 0.047494590282440186
NC4 NCC Mismatch: 0.014499999999999957

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: 0.018621576949954033
Inter Cos: 0.07477746903896332
Norm Quadratic Average: 3.338948965072632
Nearest Class Center Accuracy: 0.4234

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019359420984983444
Inter Cos: 0.058050259947776794
Norm Quadratic Average: 1.6639227867126465
Nearest Class Center Accuracy: 0.5472

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.015686405822634697
Inter Cos: 0.04571142792701721
Norm Quadratic Average: 1.289184808731079
Nearest Class Center Accuracy: 0.6263

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021374737843871117
Inter Cos: 0.04422299563884735
Norm Quadratic Average: 0.869192361831665
Nearest Class Center Accuracy: 0.7244

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04373699054121971
Inter Cos: 0.07564891129732132
Norm Quadratic Average: 0.6109517812728882
Nearest Class Center Accuracy: 0.7972

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.26093801856040955
Inter Cos: 0.26775121688842773
Norm Quadratic Average: 0.4258541166782379
Nearest Class Center Accuracy: 0.8582

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5105664134025574
Inter Cos: 0.24931123852729797
Norm Quadratic Average: 0.6806749701499939
Nearest Class Center Accuracy: 0.8802

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.209257125854492
Linear Weight Rank: 166
Intra Cos: 0.6092586517333984
Inter Cos: 0.2392832189798355
Norm Quadratic Average: 20.879718780517578
Nearest Class Center Accuracy: 0.8809

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.2224159240722656
Linear Weight Rank: 1030
Intra Cos: 0.6197137832641602
Inter Cos: 0.24991801381111145
Norm Quadratic Average: 14.356891632080078
Nearest Class Center Accuracy: 0.8807

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.2085769176483154
Linear Weight Rank: 9
Intra Cos: 0.6247515678405762
Inter Cos: 0.25935304164886475
Norm Quadratic Average: 10.116419792175293
Nearest Class Center Accuracy: 0.8809

Output Layer:
Intra Cos: 0.6286668181419373
Inter Cos: 0.2634262144565582
Norm Quadratic Average: 7.447811603546143
Nearest Class Center Accuracy: 0.8808

