Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_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: 27.691617965698242
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02513752691447735
Inter Cos: 0.10887282341718674
Norm Quadratic Average: 29.271623611450195
Nearest Class Center Accuracy: 0.31225

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027840735390782356
Inter Cos: 0.11133483052253723
Norm Quadratic Average: 23.250951766967773
Nearest Class Center Accuracy: 0.376

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03583836555480957
Inter Cos: 0.11837571859359741
Norm Quadratic Average: 26.017780303955078
Nearest Class Center Accuracy: 0.421125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.056891120970249176
Inter Cos: 0.15586085617542267
Norm Quadratic Average: 15.324539184570312
Nearest Class Center Accuracy: 0.443875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07469899207353592
Inter Cos: 0.17133693397045135
Norm Quadratic Average: 11.833907127380371
Nearest Class Center Accuracy: 0.472375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10083740949630737
Inter Cos: 0.1841689646244049
Norm Quadratic Average: 5.461606979370117
Nearest Class Center Accuracy: 0.529125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1577858328819275
Inter Cos: 0.2099429965019226
Norm Quadratic Average: 3.4850425720214844
Nearest Class Center Accuracy: 0.723125

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.49514770507812
Linear Weight Rank: 4031
Intra Cos: 0.45932796597480774
Inter Cos: 0.3484693467617035
Norm Quadratic Average: 15.051046371459961
Nearest Class Center Accuracy: 0.965875

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.394437789916992
Linear Weight Rank: 3670
Intra Cos: 0.6883578300476074
Inter Cos: 0.4961695671081543
Norm Quadratic Average: 15.271261215209961
Nearest Class Center Accuracy: 0.997375

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.0743350982666016
Linear Weight Rank: 10
Intra Cos: 0.7405893802642822
Inter Cos: 0.5759719014167786
Norm Quadratic Average: 18.886465072631836
Nearest Class Center Accuracy: 0.998375

Output Layer:
Intra Cos: 0.7741333246231079
Inter Cos: 0.6931800842285156
Norm Quadratic Average: 24.61671257019043
Nearest Class Center Accuracy: 0.993625

Test Set:
Average Loss: 2.137787971496582
Accuracy: 0.5935
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2578692138195038, Weights: 0.05096512287855148
NC2 Equiangle: Features: 0.4236520131429036, Weights: 0.21395361158582898
NC3 Self-Duality: 0.3595830202102661
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: 0.025233661755919456
Inter Cos: 0.09198884665966034
Norm Quadratic Average: 29.065229415893555
Nearest Class Center Accuracy: 0.33

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029133861884474754
Inter Cos: 0.09716958552598953
Norm Quadratic Average: 23.099241256713867
Nearest Class Center Accuracy: 0.392

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03545784950256348
Inter Cos: 0.10512372106313705
Norm Quadratic Average: 25.898048400878906
Nearest Class Center Accuracy: 0.4495

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05290330573916435
Inter Cos: 0.13812491297721863
Norm Quadratic Average: 15.256841659545898
Nearest Class Center Accuracy: 0.462

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06591183692216873
Inter Cos: 0.15018682181835175
Norm Quadratic Average: 11.800844192504883
Nearest Class Center Accuracy: 0.471

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07916104793548584
Inter Cos: 0.1585880070924759
Norm Quadratic Average: 5.436577320098877
Nearest Class Center Accuracy: 0.4895

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09883834421634674
Inter Cos: 0.17718982696533203
Norm Quadratic Average: 3.4475557804107666
Nearest Class Center Accuracy: 0.532

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.49514770507812
Linear Weight Rank: 4031
Intra Cos: 0.18224014341831207
Inter Cos: 0.30824926495552063
Norm Quadratic Average: 14.40834903717041
Nearest Class Center Accuracy: 0.5985

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.394437789916992
Linear Weight Rank: 3670
Intra Cos: 0.24366892874240875
Inter Cos: 0.4226648807525635
Norm Quadratic Average: 14.290474891662598
Nearest Class Center Accuracy: 0.5935

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.0743350982666016
Linear Weight Rank: 10
Intra Cos: 0.25155285000801086
Inter Cos: 0.490147203207016
Norm Quadratic Average: 17.58551788330078
Nearest Class Center Accuracy: 0.5755

Output Layer:
Intra Cos: 0.2700687050819397
Inter Cos: 0.5829892158508301
Norm Quadratic Average: 22.8054256439209
Nearest Class Center Accuracy: 0.561

