Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_265358_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: 0.10477277636528015
Norm Quadratic Average: 27.59717559814453
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0194343701004982
Inter Cos: 0.07326537370681763
Norm Quadratic Average: 3.9493274688720703
Nearest Class Center Accuracy: 0.40772

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02047882042825222
Inter Cos: 0.05506393685936928
Norm Quadratic Average: 1.9210261106491089
Nearest Class Center Accuracy: 0.53202

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.015700316056609154
Inter Cos: 0.043318212032318115
Norm Quadratic Average: 1.348323106765747
Nearest Class Center Accuracy: 0.62776

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025329263880848885
Inter Cos: 0.04429507628083229
Norm Quadratic Average: 0.8950361013412476
Nearest Class Center Accuracy: 0.7783

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06366533786058426
Inter Cos: 0.06262918561697006
Norm Quadratic Average: 0.6329604983329773
Nearest Class Center Accuracy: 0.90414

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.37610718607902527
Inter Cos: 0.1926691234111786
Norm Quadratic Average: 0.42401570081710815
Nearest Class Center Accuracy: 0.9959

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.8659303784370422
Inter Cos: 0.06620817631483078
Norm Quadratic Average: 0.7621378898620605
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.1370785236358643
Linear Weight Rank: 31
Intra Cos: 0.9860005974769592
Inter Cos: 0.02089603804051876
Norm Quadratic Average: 23.75826644897461
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.1413464546203613
Linear Weight Rank: 1415
Intra Cos: 0.9917178153991699
Inter Cos: 0.059318315237760544
Norm Quadratic Average: 15.905472755432129
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.1386985778808594
Linear Weight Rank: 9
Intra Cos: 0.9934824109077454
Inter Cos: 0.09004732966423035
Norm Quadratic Average: 10.823513984680176
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9945384860038757
Inter Cos: 0.16858305037021637
Norm Quadratic Average: 7.775545120239258
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.4049531819820404
Accuracy: 0.873
NC1 Within Class Collapse: 2.8047780990600586
NC2 Equinorm: Features: 0.10391367226839066, Weights: 0.002852553268894553
NC2 Equiangle: Features: 0.11679066552056207, Weights: 0.027081693543328178
NC3 Self-Duality: 0.031402938067913055
NC4 NCC Mismatch: 0.012499999999999956

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526077270507812
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: 0.018399756401777267
Inter Cos: 0.07507622241973877
Norm Quadratic Average: 3.947171688079834
Nearest Class Center Accuracy: 0.4266

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019570257514715195
Inter Cos: 0.05639956146478653
Norm Quadratic Average: 1.9217630624771118
Nearest Class Center Accuracy: 0.5417

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.014685303904116154
Inter Cos: 0.04424961283802986
Norm Quadratic Average: 1.3500425815582275
Nearest Class Center Accuracy: 0.6325

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021433070302009583
Inter Cos: 0.04529259353876114
Norm Quadratic Average: 0.8949199318885803
Nearest Class Center Accuracy: 0.7381

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04827946424484253
Inter Cos: 0.06728775799274445
Norm Quadratic Average: 0.6274058818817139
Nearest Class Center Accuracy: 0.8024

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.26519933342933655
Inter Cos: 0.2176772803068161
Norm Quadratic Average: 0.4093190133571625
Nearest Class Center Accuracy: 0.8537

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5097415447235107
Inter Cos: 0.23876099288463593
Norm Quadratic Average: 0.6983291506767273
Nearest Class Center Accuracy: 0.8727

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.1370785236358643
Linear Weight Rank: 31
Intra Cos: 0.6161897778511047
Inter Cos: 0.22127962112426758
Norm Quadratic Average: 21.04633903503418
Nearest Class Center Accuracy: 0.873

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.1413464546203613
Linear Weight Rank: 1415
Intra Cos: 0.624599277973175
Inter Cos: 0.24094238877296448
Norm Quadratic Average: 14.080245971679688
Nearest Class Center Accuracy: 0.8731

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.1386985778808594
Linear Weight Rank: 9
Intra Cos: 0.6324633359909058
Inter Cos: 0.26539599895477295
Norm Quadratic Average: 9.579869270324707
Nearest Class Center Accuracy: 0.8731

Output Layer:
Intra Cos: 0.6451876163482666
Inter Cos: 0.31054922938346863
Norm Quadratic Average: 6.900828838348389
Nearest Class Center Accuracy: 0.8731

