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_0.003.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: 0.024159565567970276
Inter Cos: 0.10449168086051941
Norm Quadratic Average: 27.958961486816406
Nearest Class Center Accuracy: 0.35208

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031212210655212402
Inter Cos: 0.11546417325735092
Norm Quadratic Average: 27.435890197753906
Nearest Class Center Accuracy: 0.41282

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03398088738322258
Inter Cos: 0.10332252830266953
Norm Quadratic Average: 34.914573669433594
Nearest Class Center Accuracy: 0.46114

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032928720116615295
Inter Cos: 0.08218725770711899
Norm Quadratic Average: 15.780648231506348
Nearest Class Center Accuracy: 0.56358

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05408642813563347
Inter Cos: 0.07666874676942825
Norm Quadratic Average: 5.8787150382995605
Nearest Class Center Accuracy: 0.661

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2097553014755249
Inter Cos: 0.2812221050262451
Norm Quadratic Average: 1.422562599182129
Nearest Class Center Accuracy: 0.80064

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5590481758117676
Inter Cos: 0.46008196473121643
Norm Quadratic Average: 1.1075035333633423
Nearest Class Center Accuracy: 0.97572

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 3.55590558052063
Linear Weight Rank: 2626
Intra Cos: 0.7085199952125549
Inter Cos: 0.4091486930847168
Norm Quadratic Average: 8.291780471801758
Nearest Class Center Accuracy: 0.99064

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.57157826423645
Linear Weight Rank: 2941
Intra Cos: 0.7671682834625244
Inter Cos: 0.3504795432090759
Norm Quadratic Average: 9.851716995239258
Nearest Class Center Accuracy: 0.99794

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.547370672225952
Linear Weight Rank: 9
Intra Cos: 0.7897630929946899
Inter Cos: 0.2661801874637604
Norm Quadratic Average: 11.566429138183594
Nearest Class Center Accuracy: 0.99946

Output Layer:
Intra Cos: 0.8189384937286377
Inter Cos: 0.2247198522090912
Norm Quadratic Average: 15.532360076904297
Nearest Class Center Accuracy: 0.9998

Test Set:
Average Loss: 0.9017105230331421
Accuracy: 0.784
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2368340790271759, Weights: 0.06942128390073776
NC2 Equiangle: Features: 0.29795246124267577, Weights: 0.15745179918077257
NC3 Self-Duality: 0.20295259356498718
NC4 NCC Mismatch: 0.06000000000000005

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: 0.024574173614382744
Inter Cos: 0.10519040375947952
Norm Quadratic Average: 27.921131134033203
Nearest Class Center Accuracy: 0.3697

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030394267290830612
Inter Cos: 0.11739460378885269
Norm Quadratic Average: 27.439851760864258
Nearest Class Center Accuracy: 0.4215

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032110314816236496
Inter Cos: 0.10525848716497421
Norm Quadratic Average: 34.94551467895508
Nearest Class Center Accuracy: 0.4666

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029758207499980927
Inter Cos: 0.08392579108476639
Norm Quadratic Average: 15.807587623596191
Nearest Class Center Accuracy: 0.5636

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04874269291758537
Inter Cos: 0.07744601368904114
Norm Quadratic Average: 5.886214256286621
Nearest Class Center Accuracy: 0.6431

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18004962801933289
Inter Cos: 0.27478617429733276
Norm Quadratic Average: 1.422480821609497
Nearest Class Center Accuracy: 0.704

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.4191606044769287
Inter Cos: 0.4440577030181885
Norm Quadratic Average: 1.097748041152954
Nearest Class Center Accuracy: 0.7606

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 3.55590558052063
Linear Weight Rank: 2626
Intra Cos: 0.4928169548511505
Inter Cos: 0.4303687810897827
Norm Quadratic Average: 8.168309211730957
Nearest Class Center Accuracy: 0.7691

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.57157826423645
Linear Weight Rank: 2941
Intra Cos: 0.4800627529621124
Inter Cos: 0.39616858959198
Norm Quadratic Average: 9.65438461303711
Nearest Class Center Accuracy: 0.7754

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.547370672225952
Linear Weight Rank: 9
Intra Cos: 0.45410287380218506
Inter Cos: 0.3468485474586487
Norm Quadratic Average: 11.287323951721191
Nearest Class Center Accuracy: 0.7783

Output Layer:
Intra Cos: 0.44953298568725586
Inter Cos: 0.32671117782592773
Norm Quadratic Average: 15.108891487121582
Nearest Class Center Accuracy: 0.7748

