Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_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: 0.021450398489832878
Inter Cos: 0.11371058225631714
Norm Quadratic Average: 27.691619873046875
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023588640615344048
Inter Cos: 0.07745176553726196
Norm Quadratic Average: 86.80841064453125
Nearest Class Center Accuracy: 0.34575

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02994741126894951
Inter Cos: 0.0841115266084671
Norm Quadratic Average: 64.98954010009766
Nearest Class Center Accuracy: 0.372875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025869304314255714
Inter Cos: 0.06601715087890625
Norm Quadratic Average: 67.91822052001953
Nearest Class Center Accuracy: 0.40275

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03610086441040039
Inter Cos: 0.08619695901870728
Norm Quadratic Average: 43.70231628417969
Nearest Class Center Accuracy: 0.42025

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034659553319215775
Inter Cos: 0.06701160967350006
Norm Quadratic Average: 44.42688751220703
Nearest Class Center Accuracy: 0.45525

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.048173222690820694
Inter Cos: 0.08511673659086227
Norm Quadratic Average: 28.472354888916016
Nearest Class Center Accuracy: 0.539125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06348280608654022
Inter Cos: 0.07520890980958939
Norm Quadratic Average: 20.075130462646484
Nearest Class Center Accuracy: 0.816875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.99113464355469
Linear Weight Rank: 4031
Intra Cos: 0.1790321171283722
Inter Cos: 0.0948437750339508
Norm Quadratic Average: 106.70281219482422
Nearest Class Center Accuracy: 0.99975

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.01712417602539
Linear Weight Rank: 3671
Intra Cos: 0.40770280361175537
Inter Cos: 0.1812782734632492
Norm Quadratic Average: 55.076839447021484
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.4869444370269775
Linear Weight Rank: 10
Intra Cos: 0.637039840221405
Inter Cos: 0.2809588611125946
Norm Quadratic Average: 38.18558120727539
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8689886331558228
Inter Cos: 0.4864422380924225
Norm Quadratic Average: 25.93604850769043
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.541048645019531
Accuracy: 0.5945
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2140384167432785, Weights: 0.02123693935573101
NC2 Equiangle: Features: 0.4204878913031684, Weights: 0.0859844896528456
NC3 Self-Duality: 0.6219194531440735
NC4 NCC Mismatch: 0.14

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352367371320724
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: 0.023172417655587196
Inter Cos: 0.07263876497745514
Norm Quadratic Average: 86.60130310058594
Nearest Class Center Accuracy: 0.3615

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02952464483678341
Inter Cos: 0.08030695468187332
Norm Quadratic Average: 64.8064193725586
Nearest Class Center Accuracy: 0.4005

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02536451257765293
Inter Cos: 0.059906113892793655
Norm Quadratic Average: 67.79285430908203
Nearest Class Center Accuracy: 0.4395

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03351178765296936
Inter Cos: 0.08550383150577545
Norm Quadratic Average: 43.6013069152832
Nearest Class Center Accuracy: 0.4375

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0310432780534029
Inter Cos: 0.06659288704395294
Norm Quadratic Average: 44.303348541259766
Nearest Class Center Accuracy: 0.4615

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03714993968605995
Inter Cos: 0.08383622020483017
Norm Quadratic Average: 28.34197425842285
Nearest Class Center Accuracy: 0.481

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03724607825279236
Inter Cos: 0.06930063664913177
Norm Quadratic Average: 19.87579345703125
Nearest Class Center Accuracy: 0.5615

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.99113464355469
Linear Weight Rank: 4031
Intra Cos: 0.05965683236718178
Inter Cos: 0.0960036963224411
Norm Quadratic Average: 102.9542465209961
Nearest Class Center Accuracy: 0.6145

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.01712417602539
Linear Weight Rank: 3671
Intra Cos: 0.11738678067922592
Inter Cos: 0.18526598811149597
Norm Quadratic Average: 51.00724792480469
Nearest Class Center Accuracy: 0.5925

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.4869444370269775
Linear Weight Rank: 10
Intra Cos: 0.17917554080486298
Inter Cos: 0.29477062821388245
Norm Quadratic Average: 34.12431335449219
Nearest Class Center Accuracy: 0.584

Output Layer:
Intra Cos: 0.25700700283050537
Inter Cos: 0.4678858518600464
Norm Quadratic Average: 22.520702362060547
Nearest Class Center Accuracy: 0.5725

