Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_weight_decay_0.03.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: 0.11371058225631714
Norm Quadratic Average: 27.691619873046875
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025960994884371758
Inter Cos: 0.10705935955047607
Norm Quadratic Average: 16.931955337524414
Nearest Class Center Accuracy: 0.3025

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029291771352291107
Inter Cos: 0.14076700806617737
Norm Quadratic Average: 9.089576721191406
Nearest Class Center Accuracy: 0.341

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04969227313995361
Inter Cos: 0.18857184052467346
Norm Quadratic Average: 8.793007850646973
Nearest Class Center Accuracy: 0.3905

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08729194849729538
Inter Cos: 0.2657926082611084
Norm Quadratic Average: 6.468681812286377
Nearest Class Center Accuracy: 0.389875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.14341045916080475
Inter Cos: 0.3650020360946655
Norm Quadratic Average: 6.547195911407471
Nearest Class Center Accuracy: 0.381375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.20477478206157684
Inter Cos: 0.4408642649650574
Norm Quadratic Average: 4.815319061279297
Nearest Class Center Accuracy: 0.3815

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2353602647781372
Inter Cos: 0.49788782000541687
Norm Quadratic Average: 3.5492396354675293
Nearest Class Center Accuracy: 0.4

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 24.00123405456543
Linear Weight Rank: 4031
Intra Cos: 0.26235419511795044
Inter Cos: 0.5314393639564514
Norm Quadratic Average: 15.225549697875977
Nearest Class Center Accuracy: 0.42825

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.801423072814941
Linear Weight Rank: 3669
Intra Cos: 0.28725680708885193
Inter Cos: 0.5801918506622314
Norm Quadratic Average: 10.113484382629395
Nearest Class Center Accuracy: 0.442375

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.654295563697815
Linear Weight Rank: 10
Intra Cos: 0.31558293104171753
Inter Cos: 0.622345507144928
Norm Quadratic Average: 7.261247634887695
Nearest Class Center Accuracy: 0.44525

Output Layer:
Intra Cos: 0.3621583878993988
Inter Cos: 0.6929854154586792
Norm Quadratic Average: 6.0891499519348145
Nearest Class Center Accuracy: 0.43

Test Set:
Average Loss: 1.453222915649414
Accuracy: 0.4335
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.24650970101356506, Weights: 0.09345469623804092
NC2 Equiangle: Features: 0.7143120659722222, Weights: 0.2820867750379774
NC3 Self-Duality: 0.3645034730434418
NC4 NCC Mismatch: 0.255

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
Inter Cos: 0.09352367371320724
Norm Quadratic Average: 27.53066635131836
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02749079279601574
Inter Cos: 0.08866699784994125
Norm Quadratic Average: 16.789581298828125
Nearest Class Center Accuracy: 0.3165

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03387390449643135
Inter Cos: 0.11871366947889328
Norm Quadratic Average: 8.976372718811035
Nearest Class Center Accuracy: 0.3455

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0535450354218483
Inter Cos: 0.16941843926906586
Norm Quadratic Average: 8.701506614685059
Nearest Class Center Accuracy: 0.398

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08607903867959976
Inter Cos: 0.24425098299980164
Norm Quadratic Average: 6.431023597717285
Nearest Class Center Accuracy: 0.4065

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.13598737120628357
Inter Cos: 0.3457333445549011
Norm Quadratic Average: 6.53079891204834
Nearest Class Center Accuracy: 0.3845

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18236057460308075
Inter Cos: 0.41959354281425476
Norm Quadratic Average: 4.807446479797363
Nearest Class Center Accuracy: 0.374

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.22025422751903534
Inter Cos: 0.4823453724384308
Norm Quadratic Average: 3.5435845851898193
Nearest Class Center Accuracy: 0.3865

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 24.00123405456543
Linear Weight Rank: 4031
Intra Cos: 0.2577146887779236
Inter Cos: 0.5390012264251709
Norm Quadratic Average: 15.230761528015137
Nearest Class Center Accuracy: 0.4165

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.801423072814941
Linear Weight Rank: 3669
Intra Cos: 0.29431506991386414
Inter Cos: 0.5904434323310852
Norm Quadratic Average: 10.143111228942871
Nearest Class Center Accuracy: 0.425

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.654295563697815
Linear Weight Rank: 10
Intra Cos: 0.32831329107284546
Inter Cos: 0.6350250840187073
Norm Quadratic Average: 7.301476001739502
Nearest Class Center Accuracy: 0.428

Output Layer:
Intra Cos: 0.38856565952301025
Inter Cos: 0.7111265063285828
Norm Quadratic Average: 6.143583297729492
Nearest Class Center Accuracy: 0.408

