Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_weight_decay_0.0007.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: 0.02625194378197193
Inter Cos: 0.10512572526931763
Norm Quadratic Average: 30.93270492553711
Nearest Class Center Accuracy: 0.310625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03490029647946358
Inter Cos: 0.11623966693878174
Norm Quadratic Average: 23.464902877807617
Nearest Class Center Accuracy: 0.36225

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0391126349568367
Inter Cos: 0.10823295265436172
Norm Quadratic Average: 27.184452056884766
Nearest Class Center Accuracy: 0.41

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05358558148145676
Inter Cos: 0.12685711681842804
Norm Quadratic Average: 16.95337677001953
Nearest Class Center Accuracy: 0.441625

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06587886065244675
Inter Cos: 0.1319817155599594
Norm Quadratic Average: 15.72781753540039
Nearest Class Center Accuracy: 0.469125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08743399381637573
Inter Cos: 0.14654380083084106
Norm Quadratic Average: 8.869638442993164
Nearest Class Center Accuracy: 0.51375

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.11812401562929153
Inter Cos: 0.15610331296920776
Norm Quadratic Average: 6.641028881072998
Nearest Class Center Accuracy: 0.688375

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.06303405761719
Linear Weight Rank: 4031
Intra Cos: 0.3144175410270691
Inter Cos: 0.2858245372772217
Norm Quadratic Average: 26.921306610107422
Nearest Class Center Accuracy: 0.96575

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.69435501098633
Linear Weight Rank: 3671
Intra Cos: 0.5953238010406494
Inter Cos: 0.44267964363098145
Norm Quadratic Average: 23.6828556060791
Nearest Class Center Accuracy: 0.99925

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.264470338821411
Linear Weight Rank: 10
Intra Cos: 0.7352826595306396
Inter Cos: 0.5457046627998352
Norm Quadratic Average: 28.107515335083008
Nearest Class Center Accuracy: 0.999875

Output Layer:
Intra Cos: 0.8267816305160522
Inter Cos: 0.710966169834137
Norm Quadratic Average: 34.955726623535156
Nearest Class Center Accuracy: 0.999

Test Set:
Average Loss: 3.021435974121094
Accuracy: 0.596
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2328757345676422, Weights: 0.041279420256614685
NC2 Equiangle: Features: 0.4358050028483073, Weights: 0.1683198928833008
NC3 Self-Duality: 0.44889602065086365
NC4 NCC Mismatch: 0.14449999999999996

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: 0.025157183408737183
Inter Cos: 0.09571027755737305
Norm Quadratic Average: 30.82242774963379
Nearest Class Center Accuracy: 0.3325

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03647631034255028
Inter Cos: 0.10913535952568054
Norm Quadratic Average: 23.38406753540039
Nearest Class Center Accuracy: 0.3775

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03990215063095093
Inter Cos: 0.1009492427110672
Norm Quadratic Average: 27.11054229736328
Nearest Class Center Accuracy: 0.429

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.052118901163339615
Inter Cos: 0.11277931928634644
Norm Quadratic Average: 16.887937545776367
Nearest Class Center Accuracy: 0.46

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06266649812459946
Inter Cos: 0.11986787617206573
Norm Quadratic Average: 15.677611351013184
Nearest Class Center Accuracy: 0.4745

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07539284229278564
Inter Cos: 0.1345357447862625
Norm Quadratic Average: 8.832846641540527
Nearest Class Center Accuracy: 0.479

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08607824146747589
Inter Cos: 0.14147526025772095
Norm Quadratic Average: 6.5818634033203125
Nearest Class Center Accuracy: 0.518

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.06303405761719
Linear Weight Rank: 4031
Intra Cos: 0.1470981389284134
Inter Cos: 0.245063915848732
Norm Quadratic Average: 25.914024353027344
Nearest Class Center Accuracy: 0.5845

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.69435501098633
Linear Weight Rank: 3671
Intra Cos: 0.22786147892475128
Inter Cos: 0.37174761295318604
Norm Quadratic Average: 22.11969757080078
Nearest Class Center Accuracy: 0.59

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.264470338821411
Linear Weight Rank: 10
Intra Cos: 0.26292720437049866
Inter Cos: 0.46104180812835693
Norm Quadratic Average: 26.027372360229492
Nearest Class Center Accuracy: 0.585

Output Layer:
Intra Cos: 0.29639047384262085
Inter Cos: 0.5896142721176147
Norm Quadratic Average: 32.20000457763672
Nearest Class Center Accuracy: 0.5595

