Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_weight_decay_0.007.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450400352478027
Inter Cos: 0.11371058970689774
Norm Quadratic Average: 27.691621780395508
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026665035635232925
Inter Cos: 0.10273081809282303
Norm Quadratic Average: 62.332096099853516
Nearest Class Center Accuracy: 0.33925

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03105982020497322
Inter Cos: 0.08929669857025146
Norm Quadratic Average: 45.23713302612305
Nearest Class Center Accuracy: 0.373875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02702074684202671
Inter Cos: 0.07102108746767044
Norm Quadratic Average: 49.2028923034668
Nearest Class Center Accuracy: 0.411625

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03433660790324211
Inter Cos: 0.07549058645963669
Norm Quadratic Average: 31.387836456298828
Nearest Class Center Accuracy: 0.435125

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03302035480737686
Inter Cos: 0.06214391440153122
Norm Quadratic Average: 32.06220626831055
Nearest Class Center Accuracy: 0.48075

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.047559741884469986
Inter Cos: 0.08398985862731934
Norm Quadratic Average: 20.617164611816406
Nearest Class Center Accuracy: 0.603875

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07403047382831573
Inter Cos: 0.08554920554161072
Norm Quadratic Average: 14.392597198486328
Nearest Class Center Accuracy: 0.9235

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.46573638916016
Linear Weight Rank: 4031
Intra Cos: 0.2527548372745514
Inter Cos: 0.12629833817481995
Norm Quadratic Average: 81.98199462890625
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.30954933166504
Linear Weight Rank: 3671
Intra Cos: 0.5687628984451294
Inter Cos: 0.24567897617816925
Norm Quadratic Average: 39.50480651855469
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.041130781173706
Linear Weight Rank: 10
Intra Cos: 0.7839202880859375
Inter Cos: 0.31647738814353943
Norm Quadratic Average: 26.030263900756836
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9057945013046265
Inter Cos: 0.48336923122406006
Norm Quadratic Average: 16.81778907775879
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.7443860549926757
Accuracy: 0.591
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20889776945114136, Weights: 0.02068164013326168
NC2 Equiangle: Features: 0.4529973347981771, Weights: 0.09477456410725911
NC3 Self-Duality: 0.5558409690856934
NC4 NCC Mismatch: 0.14649999999999996

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
Inter Cos: 0.09352368116378784
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: 0.02456505410373211
Inter Cos: 0.09038905054330826
Norm Quadratic Average: 62.30678939819336
Nearest Class Center Accuracy: 0.3555

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029542503878474236
Inter Cos: 0.08688369393348694
Norm Quadratic Average: 45.23194885253906
Nearest Class Center Accuracy: 0.3985

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026637153699994087
Inter Cos: 0.06536201387643814
Norm Quadratic Average: 49.24116516113281
Nearest Class Center Accuracy: 0.4305

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03222707286477089
Inter Cos: 0.07618769258260727
Norm Quadratic Average: 31.378700256347656
Nearest Class Center Accuracy: 0.4475

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02981962077319622
Inter Cos: 0.06256679445505142
Norm Quadratic Average: 32.03820037841797
Nearest Class Center Accuracy: 0.4815

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03495379909873009
Inter Cos: 0.07633616775274277
Norm Quadratic Average: 20.55986213684082
Nearest Class Center Accuracy: 0.5055

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.037728115916252136
Inter Cos: 0.08153796941041946
Norm Quadratic Average: 14.259016036987305
Nearest Class Center Accuracy: 0.59

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.46573638916016
Linear Weight Rank: 4031
Intra Cos: 0.07791192829608917
Inter Cos: 0.1369183361530304
Norm Quadratic Average: 77.9707260131836
Nearest Class Center Accuracy: 0.618

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.30954933166504
Linear Weight Rank: 3671
Intra Cos: 0.1677856594324112
Inter Cos: 0.2577374577522278
Norm Quadratic Average: 35.42231369018555
Nearest Class Center Accuracy: 0.596

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.041130781173706
Linear Weight Rank: 10
Intra Cos: 0.23505578935146332
Inter Cos: 0.36621683835983276
Norm Quadratic Average: 22.571651458740234
Nearest Class Center Accuracy: 0.5865

Output Layer:
Intra Cos: 0.28776854276657104
Inter Cos: 0.48069238662719727
Norm Quadratic Average: 14.362905502319336
Nearest Class Center Accuracy: 0.5715

