Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_314159_test_samples_None_train_samples_None_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: 0.01989092119038105
Inter Cos: 0.10477276146411896
Norm Quadratic Average: 27.59718132019043
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023191411048173904
Inter Cos: 0.10748594254255295
Norm Quadratic Average: 24.851015090942383
Nearest Class Center Accuracy: 0.3409

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030463458970189095
Inter Cos: 0.11292838305234909
Norm Quadratic Average: 17.976343154907227
Nearest Class Center Accuracy: 0.42502

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03119492158293724
Inter Cos: 0.08994373679161072
Norm Quadratic Average: 10.098329544067383
Nearest Class Center Accuracy: 0.53324

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.052619222551584244
Inter Cos: 0.10177025943994522
Norm Quadratic Average: 1.9127781391143799
Nearest Class Center Accuracy: 0.63856

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2798040509223938
Inter Cos: 0.4076160490512848
Norm Quadratic Average: 0.6970568299293518
Nearest Class Center Accuracy: 0.74158

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5011675953865051
Inter Cos: 0.4844572842121124
Norm Quadratic Average: 0.617713212966919
Nearest Class Center Accuracy: 0.9199

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.6666721105575562
Inter Cos: 0.5002208948135376
Norm Quadratic Average: 1.0085878372192383
Nearest Class Center Accuracy: 0.98436

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.9915478229522705
Linear Weight Rank: 6
Intra Cos: 0.7174525260925293
Inter Cos: 0.4471520483493805
Norm Quadratic Average: 8.642378807067871
Nearest Class Center Accuracy: 0.99596

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.9914419651031494
Linear Weight Rank: 2738
Intra Cos: 0.73740553855896
Inter Cos: 0.40422025322914124
Norm Quadratic Average: 10.663911819458008
Nearest Class Center Accuracy: 0.99844

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.989820718765259
Linear Weight Rank: 9
Intra Cos: 0.7740470170974731
Inter Cos: 0.3701060712337494
Norm Quadratic Average: 12.12061595916748
Nearest Class Center Accuracy: 0.99928

Output Layer:
Intra Cos: 0.8030561208724976
Inter Cos: 0.41275855898857117
Norm Quadratic Average: 15.762696266174316
Nearest Class Center Accuracy: 0.99964

Test Set:
Average Loss: 0.8994608543395997
Accuracy: 0.7631
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2575221359729767, Weights: 0.05928671360015869
NC2 Equiangle: Features: 0.3853078206380208, Weights: 0.2441639158460829
NC3 Self-Duality: 0.22663576900959015
NC4 NCC Mismatch: 0.06889999999999996

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526073545217514
Inter Cos: 0.1042705774307251
Norm Quadratic Average: 27.550134658813477
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02387956716120243
Inter Cos: 0.10829606652259827
Norm Quadratic Average: 24.81192970275879
Nearest Class Center Accuracy: 0.3573

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029560459777712822
Inter Cos: 0.11424301564693451
Norm Quadratic Average: 17.985456466674805
Nearest Class Center Accuracy: 0.4354

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02958575077354908
Inter Cos: 0.09045248478651047
Norm Quadratic Average: 10.115011215209961
Nearest Class Center Accuracy: 0.5383

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.047189611941576004
Inter Cos: 0.10277609527111053
Norm Quadratic Average: 1.9156548976898193
Nearest Class Center Accuracy: 0.6275

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2462749183177948
Inter Cos: 0.4039756655693054
Norm Quadratic Average: 0.6966408491134644
Nearest Class Center Accuracy: 0.6636

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.36137428879737854
Inter Cos: 0.4832295775413513
Norm Quadratic Average: 0.6123884916305542
Nearest Class Center Accuracy: 0.7246

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.4463733732700348
Inter Cos: 0.5116314888000488
Norm Quadratic Average: 0.9930618405342102
Nearest Class Center Accuracy: 0.7567

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.9915478229522705
Linear Weight Rank: 6
Intra Cos: 0.43423330783843994
Inter Cos: 0.47572922706604004
Norm Quadratic Average: 8.46873950958252
Nearest Class Center Accuracy: 0.7601

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.9914419651031494
Linear Weight Rank: 2738
Intra Cos: 0.4119391143321991
Inter Cos: 0.43138694763183594
Norm Quadratic Average: 10.40972900390625
Nearest Class Center Accuracy: 0.7543

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.989820718765259
Linear Weight Rank: 9
Intra Cos: 0.4090520739555359
Inter Cos: 0.3929694592952728
Norm Quadratic Average: 11.782760620117188
Nearest Class Center Accuracy: 0.7517

Output Layer:
Intra Cos: 0.3845639228820801
Inter Cos: 0.3753508925437927
Norm Quadratic Average: 15.27518367767334
Nearest Class Center Accuracy: 0.748

