Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_265358_test_samples_None_train_samples_None_weight_decay_0.02.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: 0.10477277636528015
Norm Quadratic Average: 27.59717559814453
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01927158609032631
Inter Cos: 0.07188264280557632
Norm Quadratic Average: 3.2563235759735107
Nearest Class Center Accuracy: 0.40922

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02014186978340149
Inter Cos: 0.053512878715991974
Norm Quadratic Average: 1.5891228914260864
Nearest Class Center Accuracy: 0.53018

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.016640618443489075
Inter Cos: 0.048040010035037994
Norm Quadratic Average: 1.119016408920288
Nearest Class Center Accuracy: 0.62574

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029932457953691483
Inter Cos: 0.050871651619672775
Norm Quadratic Average: 0.8064252138137817
Nearest Class Center Accuracy: 0.76822

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05596456676721573
Inter Cos: 0.06158960610628128
Norm Quadratic Average: 0.6732061505317688
Nearest Class Center Accuracy: 0.88242

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.25749439001083374
Inter Cos: 0.22362813353538513
Norm Quadratic Average: 0.4182441234588623
Nearest Class Center Accuracy: 0.98194

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.830610454082489
Inter Cos: 0.22439295053482056
Norm Quadratic Average: 0.6114619970321655
Nearest Class Center Accuracy: 0.99994

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.0451014041900635
Linear Weight Rank: 10
Intra Cos: 0.9794375896453857
Inter Cos: 0.182816281914711
Norm Quadratic Average: 22.74175262451172
Nearest Class Center Accuracy: 0.99998

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.047633171081543
Linear Weight Rank: 1598
Intra Cos: 0.9869089722633362
Inter Cos: 0.19527332484722137
Norm Quadratic Average: 15.270129203796387
Nearest Class Center Accuracy: 0.99998

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.0472965240478516
Linear Weight Rank: 9
Intra Cos: 0.9898335337638855
Inter Cos: 0.18670955300331116
Norm Quadratic Average: 10.492374420166016
Nearest Class Center Accuracy: 0.99998

Output Layer:
Intra Cos: 0.9924076795578003
Inter Cos: 0.16143518686294556
Norm Quadratic Average: 7.661890506744385
Nearest Class Center Accuracy: 0.99998

Test Set:
Average Loss: 0.43828364367485045
Accuracy: 0.8656
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.10958345979452133, Weights: 0.0049684843979775906
NC2 Equiangle: Features: 0.1505171987745497, Weights: 0.09850298563639323
NC3 Self-Duality: 0.05113058164715767
NC4 NCC Mismatch: 0.010700000000000043

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: 27.550134658813477
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018307026475667953
Inter Cos: 0.07394127547740936
Norm Quadratic Average: 3.2551016807556152
Nearest Class Center Accuracy: 0.4279

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019127050414681435
Inter Cos: 0.05535547807812691
Norm Quadratic Average: 1.5898048877716064
Nearest Class Center Accuracy: 0.5437

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.015671050176024437
Inter Cos: 0.04946347698569298
Norm Quadratic Average: 1.1205331087112427
Nearest Class Center Accuracy: 0.6292

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02545342408120632
Inter Cos: 0.051817961037158966
Norm Quadratic Average: 0.8067598342895508
Nearest Class Center Accuracy: 0.7262

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.042941126972436905
Inter Cos: 0.06488441675901413
Norm Quadratic Average: 0.6695061922073364
Nearest Class Center Accuracy: 0.7842

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18159176409244537
Inter Cos: 0.22744065523147583
Norm Quadratic Average: 0.41043534874916077
Nearest Class Center Accuracy: 0.8318

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.48405560851097107
Inter Cos: 0.2854832410812378
Norm Quadratic Average: 0.5665510296821594
Nearest Class Center Accuracy: 0.8627

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.0451014041900635
Linear Weight Rank: 10
Intra Cos: 0.5809685587882996
Inter Cos: 0.3203429877758026
Norm Quadratic Average: 20.292823791503906
Nearest Class Center Accuracy: 0.8652

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.047633171081543
Linear Weight Rank: 1598
Intra Cos: 0.5955712199211121
Inter Cos: 0.3336986303329468
Norm Quadratic Average: 13.625556945800781
Nearest Class Center Accuracy: 0.8652

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.0472965240478516
Linear Weight Rank: 9
Intra Cos: 0.6060304045677185
Inter Cos: 0.33588436245918274
Norm Quadratic Average: 9.355597496032715
Nearest Class Center Accuracy: 0.8653

Output Layer:
Intra Cos: 0.6292307376861572
Inter Cos: 0.3211522102355957
Norm Quadratic Average: 6.843040466308594
Nearest Class Center Accuracy: 0.865

