Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_979323_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: 0.0198909230530262
Inter Cos: 0.10477276891469955
Norm Quadratic Average: 27.59718894958496
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023578470572829247
Inter Cos: 0.10190516710281372
Norm Quadratic Average: 27.490619659423828
Nearest Class Center Accuracy: 0.35504

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030440591275691986
Inter Cos: 0.11097244918346405
Norm Quadratic Average: 27.239002227783203
Nearest Class Center Accuracy: 0.41384

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03423144668340683
Inter Cos: 0.1023801788687706
Norm Quadratic Average: 33.86616897583008
Nearest Class Center Accuracy: 0.4661

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034375376999378204
Inter Cos: 0.08235520124435425
Norm Quadratic Average: 14.65832805633545
Nearest Class Center Accuracy: 0.5642

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05931031331419945
Inter Cos: 0.08041723072528839
Norm Quadratic Average: 5.358010292053223
Nearest Class Center Accuracy: 0.66784

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.23541881144046783
Inter Cos: 0.28833410143852234
Norm Quadratic Average: 1.3588007688522339
Nearest Class Center Accuracy: 0.81032

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5721692442893982
Inter Cos: 0.44726699590682983
Norm Quadratic Average: 1.1086245775222778
Nearest Class Center Accuracy: 0.97606

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 3.559868812561035
Linear Weight Rank: 2626
Intra Cos: 0.7131780385971069
Inter Cos: 0.4145742654800415
Norm Quadratic Average: 8.240286827087402
Nearest Class Center Accuracy: 0.9919

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.5759289264678955
Linear Weight Rank: 2927
Intra Cos: 0.7638487219810486
Inter Cos: 0.37157633900642395
Norm Quadratic Average: 9.806085586547852
Nearest Class Center Accuracy: 0.9984

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.5517594814300537
Linear Weight Rank: 9
Intra Cos: 0.7832825779914856
Inter Cos: 0.2969604730606079
Norm Quadratic Average: 11.520256042480469
Nearest Class Center Accuracy: 0.9994

Output Layer:
Intra Cos: 0.8001189827919006
Inter Cos: 0.2793610095977783
Norm Quadratic Average: 15.430553436279297
Nearest Class Center Accuracy: 0.99982

Test Set:
Average Loss: 0.9153726643562317
Accuracy: 0.78
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.23946011066436768, Weights: 0.06884954869747162
NC2 Equiangle: Features: 0.2998883777194553, Weights: 0.15684336556328668
NC3 Self-Duality: 0.20388920605182648
NC4 NCC Mismatch: 0.06259999999999999

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: 27.550140380859375
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024103155359625816
Inter Cos: 0.10264858603477478
Norm Quadratic Average: 27.45339012145996
Nearest Class Center Accuracy: 0.3725

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029598569497466087
Inter Cos: 0.11303640902042389
Norm Quadratic Average: 27.242223739624023
Nearest Class Center Accuracy: 0.4237

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03245500102639198
Inter Cos: 0.10440531373023987
Norm Quadratic Average: 33.898284912109375
Nearest Class Center Accuracy: 0.474

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03116707131266594
Inter Cos: 0.08402664214372635
Norm Quadratic Average: 14.684091567993164
Nearest Class Center Accuracy: 0.5631

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.053171560168266296
Inter Cos: 0.08082190901041031
Norm Quadratic Average: 5.365004539489746
Nearest Class Center Accuracy: 0.6482

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.20231488347053528
Inter Cos: 0.2826503813266754
Norm Quadratic Average: 1.3575681447982788
Nearest Class Center Accuracy: 0.7065

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.4185430407524109
Inter Cos: 0.4266207218170166
Norm Quadratic Average: 1.0971251726150513
Nearest Class Center Accuracy: 0.7601

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 3.559868812561035
Linear Weight Rank: 2626
Intra Cos: 0.49270498752593994
Inter Cos: 0.4268605709075928
Norm Quadratic Average: 8.102131843566895
Nearest Class Center Accuracy: 0.7701

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.5759289264678955
Linear Weight Rank: 2927
Intra Cos: 0.4798707664012909
Inter Cos: 0.39288589358329773
Norm Quadratic Average: 9.59377384185791
Nearest Class Center Accuracy: 0.7756

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.5517594814300537
Linear Weight Rank: 9
Intra Cos: 0.4550045430660248
Inter Cos: 0.34468135237693787
Norm Quadratic Average: 11.22538948059082
Nearest Class Center Accuracy: 0.7759

Output Layer:
Intra Cos: 0.44048550724983215
Inter Cos: 0.31839317083358765
Norm Quadratic Average: 14.990063667297363
Nearest Class Center Accuracy: 0.7753

