Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_weight_decay_0.003.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: 27.691617965698242
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023212075233459473
Inter Cos: 0.0995197668671608
Norm Quadratic Average: 76.68243408203125
Nearest Class Center Accuracy: 0.348875

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02642117254436016
Inter Cos: 0.09580843150615692
Norm Quadratic Average: 57.33419418334961
Nearest Class Center Accuracy: 0.37525

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02274707704782486
Inter Cos: 0.06869909167289734
Norm Quadratic Average: 60.73461151123047
Nearest Class Center Accuracy: 0.405875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030664388090372086
Inter Cos: 0.0804901048541069
Norm Quadratic Average: 38.3531608581543
Nearest Class Center Accuracy: 0.432125

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02960989810526371
Inter Cos: 0.07299590110778809
Norm Quadratic Average: 39.18037414550781
Nearest Class Center Accuracy: 0.473125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.041578590869903564
Inter Cos: 0.07853975892066956
Norm Quadratic Average: 24.86725616455078
Nearest Class Center Accuracy: 0.570875

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06606365740299225
Inter Cos: 0.07797054946422577
Norm Quadratic Average: 17.808313369750977
Nearest Class Center Accuracy: 0.867125

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 87.79473876953125
Linear Weight Rank: 4031
Intra Cos: 0.20076587796211243
Inter Cos: 0.1024312898516655
Norm Quadratic Average: 97.04021453857422
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 35.496097564697266
Linear Weight Rank: 3670
Intra Cos: 0.4606408476829529
Inter Cos: 0.2021040916442871
Norm Quadratic Average: 47.86181640625
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.274982213973999
Linear Weight Rank: 10
Intra Cos: 0.6968787312507629
Inter Cos: 0.2985611855983734
Norm Quadratic Average: 31.946123123168945
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8824596405029297
Inter Cos: 0.4383009970188141
Norm Quadratic Average: 21.010648727416992
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.0832055206298827
Accuracy: 0.591
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.21406741440296173, Weights: 0.01699228771030903
NC2 Equiangle: Features: 0.42198850843641494, Weights: 0.09071695539686415
NC3 Self-Duality: 0.6040806770324707
NC4 NCC Mismatch: 0.15500000000000003

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
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: 0.022659335285425186
Inter Cos: 0.08738401532173157
Norm Quadratic Average: 76.31269073486328
Nearest Class Center Accuracy: 0.371

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026434360072016716
Inter Cos: 0.08473572134971619
Norm Quadratic Average: 57.05229568481445
Nearest Class Center Accuracy: 0.398

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021814359351992607
Inter Cos: 0.06069031357765198
Norm Quadratic Average: 60.51908493041992
Nearest Class Center Accuracy: 0.4405

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026987185701727867
Inter Cos: 0.07193045318126678
Norm Quadratic Average: 38.19721603393555
Nearest Class Center Accuracy: 0.4565

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025718379765748978
Inter Cos: 0.06504015624523163
Norm Quadratic Average: 39.06486892700195
Nearest Class Center Accuracy: 0.492

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030012713745236397
Inter Cos: 0.0683116614818573
Norm Quadratic Average: 24.73996925354004
Nearest Class Center Accuracy: 0.5085

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03426216542720795
Inter Cos: 0.07469449192285538
Norm Quadratic Average: 17.632230758666992
Nearest Class Center Accuracy: 0.578

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 87.79473876953125
Linear Weight Rank: 4031
Intra Cos: 0.06332788616418839
Inter Cos: 0.11671342700719833
Norm Quadratic Average: 93.23668670654297
Nearest Class Center Accuracy: 0.619

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 35.496097564697266
Linear Weight Rank: 3670
Intra Cos: 0.12980520725250244
Inter Cos: 0.22424204647541046
Norm Quadratic Average: 43.77718734741211
Nearest Class Center Accuracy: 0.5965

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.274982213973999
Linear Weight Rank: 10
Intra Cos: 0.1987752616405487
Inter Cos: 0.341033011674881
Norm Quadratic Average: 28.096256256103516
Nearest Class Center Accuracy: 0.5785

Output Layer:
Intra Cos: 0.28014177083969116
Inter Cos: 0.5012120008468628
Norm Quadratic Average: 18.001081466674805
Nearest Class Center Accuracy: 0.5595

