Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_weight_decay_0.0003.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: 0.02635468915104866
Inter Cos: 0.10510824620723724
Norm Quadratic Average: 30.751869201660156
Nearest Class Center Accuracy: 0.3125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03545980900526047
Inter Cos: 0.11666394770145416
Norm Quadratic Average: 23.425373077392578
Nearest Class Center Accuracy: 0.361875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03970809280872345
Inter Cos: 0.10838381946086884
Norm Quadratic Average: 27.361167907714844
Nearest Class Center Accuracy: 0.410875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05490901321172714
Inter Cos: 0.127251997590065
Norm Quadratic Average: 17.27229881286621
Nearest Class Center Accuracy: 0.442

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06687989085912704
Inter Cos: 0.13120049238204956
Norm Quadratic Average: 16.152936935424805
Nearest Class Center Accuracy: 0.469125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09032271057367325
Inter Cos: 0.147613063454628
Norm Quadratic Average: 9.192399978637695
Nearest Class Center Accuracy: 0.517375

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12394014745950699
Inter Cos: 0.16162395477294922
Norm Quadratic Average: 6.947659015655518
Nearest Class Center Accuracy: 0.6975

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.96076202392578
Linear Weight Rank: 4031
Intra Cos: 0.31952548027038574
Inter Cos: 0.28724128007888794
Norm Quadratic Average: 28.481592178344727
Nearest Class Center Accuracy: 0.964875

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.45927047729492
Linear Weight Rank: 3671
Intra Cos: 0.5987494587898254
Inter Cos: 0.4430953860282898
Norm Quadratic Average: 24.988658905029297
Nearest Class Center Accuracy: 0.99925

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2799298763275146
Linear Weight Rank: 10
Intra Cos: 0.7403778433799744
Inter Cos: 0.5443657040596008
Norm Quadratic Average: 29.587190628051758
Nearest Class Center Accuracy: 0.99975

Output Layer:
Intra Cos: 0.8277366161346436
Inter Cos: 0.7098138332366943
Norm Quadratic Average: 36.787193298339844
Nearest Class Center Accuracy: 0.998875

Test Set:
Average Loss: 3.1091188507080076
Accuracy: 0.5925
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.23810578882694244, Weights: 0.041977908462285995
NC2 Equiangle: Features: 0.4337286207411024, Weights: 0.16739251878526476
NC3 Self-Duality: 0.4583408534526825
NC4 NCC Mismatch: 0.14049999999999996

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: 0.025154344737529755
Inter Cos: 0.09679163992404938
Norm Quadratic Average: 30.650218963623047
Nearest Class Center Accuracy: 0.3355

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03704921528697014
Inter Cos: 0.11138097941875458
Norm Quadratic Average: 23.35038185119629
Nearest Class Center Accuracy: 0.3785

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04037611186504364
Inter Cos: 0.10235925763845444
Norm Quadratic Average: 27.293737411499023
Nearest Class Center Accuracy: 0.4325

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05325673520565033
Inter Cos: 0.11503134667873383
Norm Quadratic Average: 17.20606231689453
Nearest Class Center Accuracy: 0.463

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06357025355100632
Inter Cos: 0.12046310305595398
Norm Quadratic Average: 16.101043701171875
Nearest Class Center Accuracy: 0.478

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07838432490825653
Inter Cos: 0.13446177542209625
Norm Quadratic Average: 9.155041694641113
Nearest Class Center Accuracy: 0.4795

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09087110310792923
Inter Cos: 0.14234501123428345
Norm Quadratic Average: 6.8828043937683105
Nearest Class Center Accuracy: 0.5265

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.96076202392578
Linear Weight Rank: 4031
Intra Cos: 0.14804381132125854
Inter Cos: 0.24723191559314728
Norm Quadratic Average: 27.39613914489746
Nearest Class Center Accuracy: 0.5795

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.45927047729492
Linear Weight Rank: 3671
Intra Cos: 0.22403542697429657
Inter Cos: 0.3707521855831146
Norm Quadratic Average: 23.3253116607666
Nearest Class Center Accuracy: 0.587

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2799298763275146
Linear Weight Rank: 10
Intra Cos: 0.25787192583084106
Inter Cos: 0.4563910961151123
Norm Quadratic Average: 27.38541603088379
Nearest Class Center Accuracy: 0.5765

Output Layer:
Intra Cos: 0.28488588333129883
Inter Cos: 0.5807505249977112
Norm Quadratic Average: 33.900238037109375
Nearest Class Center Accuracy: 0.5615

