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_0.0003.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: 0.022778687998652458
Inter Cos: 0.08650775998830795
Norm Quadratic Average: 25.199115753173828
Nearest Class Center Accuracy: 0.3931

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026713743805885315
Inter Cos: 0.08609220385551453
Norm Quadratic Average: 23.565515518188477
Nearest Class Center Accuracy: 0.48622

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02824825793504715
Inter Cos: 0.07269994169473648
Norm Quadratic Average: 28.66852378845215
Nearest Class Center Accuracy: 0.56692

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03324460610747337
Inter Cos: 0.062134187668561935
Norm Quadratic Average: 14.714361190795898
Nearest Class Center Accuracy: 0.65868

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04891999438405037
Inter Cos: 0.06106875091791153
Norm Quadratic Average: 9.587525367736816
Nearest Class Center Accuracy: 0.72612

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12256208062171936
Inter Cos: 0.12669788300991058
Norm Quadratic Average: 3.792787790298462
Nearest Class Center Accuracy: 0.85002

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.4057183861732483
Inter Cos: 0.2389805018901825
Norm Quadratic Average: 2.3488054275512695
Nearest Class Center Accuracy: 0.99032

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.55327606201172
Linear Weight Rank: 4031
Intra Cos: 0.748318076133728
Inter Cos: 0.2685105502605438
Norm Quadratic Average: 14.39722728729248
Nearest Class Center Accuracy: 0.99844

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.96753978729248
Linear Weight Rank: 3669
Intra Cos: 0.8229329586029053
Inter Cos: 0.18732966482639313
Norm Quadratic Average: 14.671121597290039
Nearest Class Center Accuracy: 0.99974

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.611980676651001
Linear Weight Rank: 10
Intra Cos: 0.8441264629364014
Inter Cos: 0.14678098261356354
Norm Quadratic Average: 16.13574981689453
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8649042248725891
Inter Cos: 0.2838101387023926
Norm Quadratic Average: 19.52545738220215
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.0248228747367858
Accuracy: 0.8151
NC1 Within Class Collapse: 6.251957893371582
NC2 Equinorm: Features: 0.20420242846012115, Weights: 0.034653231501579285
NC2 Equiangle: Features: 0.19719000922309027, Weights: 0.07456541591220432
NC3 Self-Duality: 0.1655769795179367
NC4 NCC Mismatch: 0.04959999999999998

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: 0.021094517782330513
Inter Cos: 0.08728154748678207
Norm Quadratic Average: 25.18295669555664
Nearest Class Center Accuracy: 0.4099

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02506057731807232
Inter Cos: 0.08766890317201614
Norm Quadratic Average: 23.573253631591797
Nearest Class Center Accuracy: 0.489

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02615187130868435
Inter Cos: 0.07362131774425507
Norm Quadratic Average: 28.693195343017578
Nearest Class Center Accuracy: 0.5697

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029594101011753082
Inter Cos: 0.06326653063297272
Norm Quadratic Average: 14.733154296875
Nearest Class Center Accuracy: 0.6425

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04279303923249245
Inter Cos: 0.06301996111869812
Norm Quadratic Average: 9.590929985046387
Nearest Class Center Accuracy: 0.6866

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10145985335111618
Inter Cos: 0.13135339319705963
Norm Quadratic Average: 3.7826521396636963
Nearest Class Center Accuracy: 0.7393

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2711048722267151
Inter Cos: 0.26059237122535706
Norm Quadratic Average: 2.3107290267944336
Nearest Class Center Accuracy: 0.8

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.55327606201172
Linear Weight Rank: 4031
Intra Cos: 0.44981762766838074
Inter Cos: 0.34375807642936707
Norm Quadratic Average: 13.912419319152832
Nearest Class Center Accuracy: 0.804

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.96753978729248
Linear Weight Rank: 3669
Intra Cos: 0.46614232659339905
Inter Cos: 0.31880393624305725
Norm Quadratic Average: 14.060425758361816
Nearest Class Center Accuracy: 0.8063

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.611980676651001
Linear Weight Rank: 10
Intra Cos: 0.461101233959198
Inter Cos: 0.3009183406829834
Norm Quadratic Average: 15.42760944366455
Nearest Class Center Accuracy: 0.8101

Output Layer:
Intra Cos: 0.48004791140556335
Inter Cos: 0.3361624479293823
Norm Quadratic Average: 18.64785385131836
Nearest Class Center Accuracy: 0.8091

