Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_314159_weight_decay_0.01.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: 0.02264988422393799
Inter Cos: 0.10154129564762115
Norm Quadratic Average: 54.17412567138672
Nearest Class Center Accuracy: 0.325125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025378424674272537
Inter Cos: 0.0870104432106018
Norm Quadratic Average: 40.42094802856445
Nearest Class Center Accuracy: 0.360125

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023471469059586525
Inter Cos: 0.07022486627101898
Norm Quadratic Average: 42.605194091796875
Nearest Class Center Accuracy: 0.39325

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031617164611816406
Inter Cos: 0.07549264281988144
Norm Quadratic Average: 26.886524200439453
Nearest Class Center Accuracy: 0.42375

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03232574835419655
Inter Cos: 0.06626184284687042
Norm Quadratic Average: 27.575260162353516
Nearest Class Center Accuracy: 0.471125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04765985533595085
Inter Cos: 0.07430952787399292
Norm Quadratic Average: 17.395112991333008
Nearest Class Center Accuracy: 0.608

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08882077783346176
Inter Cos: 0.08446268737316132
Norm Quadratic Average: 12.283910751342773
Nearest Class Center Accuracy: 0.95225

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.74085998535156
Linear Weight Rank: 4031
Intra Cos: 0.3270610272884369
Inter Cos: 0.13060761988162994
Norm Quadratic Average: 74.1467514038086
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.380327224731445
Linear Weight Rank: 3670
Intra Cos: 0.6843680143356323
Inter Cos: 0.23823410272598267
Norm Quadratic Average: 35.57892608642578
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.9050562381744385
Linear Weight Rank: 10
Intra Cos: 0.8500008583068848
Inter Cos: 0.31942301988601685
Norm Quadratic Average: 23.43075180053711
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9156255125999451
Inter Cos: 0.4213026165962219
Norm Quadratic Average: 15.111814498901367
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.6544718017578126
Accuracy: 0.588
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.1991174966096878, Weights: 0.017720989882946014
NC2 Equiangle: Features: 0.3969696044921875, Weights: 0.11325111389160156
NC3 Self-Duality: 0.48426133394241333
NC4 NCC Mismatch: 0.14400000000000002

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: 0.021862339228391647
Inter Cos: 0.08842980861663818
Norm Quadratic Average: 54.00032424926758
Nearest Class Center Accuracy: 0.351

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025626052170991898
Inter Cos: 0.07713013142347336
Norm Quadratic Average: 40.270599365234375
Nearest Class Center Accuracy: 0.377

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024606702849268913
Inter Cos: 0.061899106949567795
Norm Quadratic Average: 42.51446533203125
Nearest Class Center Accuracy: 0.414

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02898026816546917
Inter Cos: 0.06673721969127655
Norm Quadratic Average: 26.81535530090332
Nearest Class Center Accuracy: 0.4455

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028317583724856377
Inter Cos: 0.05732465907931328
Norm Quadratic Average: 27.498302459716797
Nearest Class Center Accuracy: 0.481

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03178676590323448
Inter Cos: 0.0689387246966362
Norm Quadratic Average: 17.299604415893555
Nearest Class Center Accuracy: 0.5065

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03779812157154083
Inter Cos: 0.08140838146209717
Norm Quadratic Average: 12.136980056762695
Nearest Class Center Accuracy: 0.588

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.74085998535156
Linear Weight Rank: 4031
Intra Cos: 0.08277739584445953
Inter Cos: 0.15560677647590637
Norm Quadratic Average: 69.82132720947266
Nearest Class Center Accuracy: 0.606

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.380327224731445
Linear Weight Rank: 3670
Intra Cos: 0.17175188660621643
Inter Cos: 0.3024059534072876
Norm Quadratic Average: 31.297170639038086
Nearest Class Center Accuracy: 0.586

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.9050562381744385
Linear Weight Rank: 10
Intra Cos: 0.22640609741210938
Inter Cos: 0.4016590714454651
Norm Quadratic Average: 19.993202209472656
Nearest Class Center Accuracy: 0.574

Output Layer:
Intra Cos: 0.2548951208591461
Inter Cos: 0.48262086510658264
Norm Quadratic Average: 12.70789623260498
Nearest Class Center Accuracy: 0.5635

