Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_weight_decay_0.007.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450398489832878
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: 0.023191308602690697
Inter Cos: 0.07704173028469086
Norm Quadratic Average: 63.54800796508789
Nearest Class Center Accuracy: 0.344

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02935614250600338
Inter Cos: 0.08547830581665039
Norm Quadratic Average: 47.62036895751953
Nearest Class Center Accuracy: 0.372

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024558452889323235
Inter Cos: 0.0639081671833992
Norm Quadratic Average: 49.62343215942383
Nearest Class Center Accuracy: 0.4045

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03462089225649834
Inter Cos: 0.08270715922117233
Norm Quadratic Average: 31.958948135375977
Nearest Class Center Accuracy: 0.428375

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032374873757362366
Inter Cos: 0.06316316872835159
Norm Quadratic Average: 32.405208587646484
Nearest Class Center Accuracy: 0.468125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04702557995915413
Inter Cos: 0.07723469287157059
Norm Quadratic Average: 20.468591690063477
Nearest Class Center Accuracy: 0.58975

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07476086169481277
Inter Cos: 0.07897719740867615
Norm Quadratic Average: 14.456472396850586
Nearest Class Center Accuracy: 0.919375

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.46818542480469
Linear Weight Rank: 4031
Intra Cos: 0.2545115351676941
Inter Cos: 0.12135941535234451
Norm Quadratic Average: 81.88272857666016
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.30665397644043
Linear Weight Rank: 3671
Intra Cos: 0.5654852986335754
Inter Cos: 0.22563591599464417
Norm Quadratic Average: 39.16339874267578
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.027357578277588
Linear Weight Rank: 10
Intra Cos: 0.7823166847229004
Inter Cos: 0.31234270334243774
Norm Quadratic Average: 25.591838836669922
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.897037923336029
Inter Cos: 0.4691182076931
Norm Quadratic Average: 16.09937858581543
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.6846499710083007
Accuracy: 0.6
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20361831784248352, Weights: 0.01632203720510006
NC2 Equiangle: Features: 0.42195811801486544, Weights: 0.09118285708957248
NC3 Self-Duality: 0.5369755029678345
NC4 NCC Mismatch: 0.14149999999999996

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352367371320724
Norm Quadratic Average: 27.530664443969727
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02289362996816635
Inter Cos: 0.07093452662229538
Norm Quadratic Average: 63.3722038269043
Nearest Class Center Accuracy: 0.3575

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029107028618454933
Inter Cos: 0.08178362250328064
Norm Quadratic Average: 47.48869705200195
Nearest Class Center Accuracy: 0.398

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023799365386366844
Inter Cos: 0.060171082615852356
Norm Quadratic Average: 49.537010192871094
Nearest Class Center Accuracy: 0.437

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031740058213472366
Inter Cos: 0.08242510259151459
Norm Quadratic Average: 31.8831787109375
Nearest Class Center Accuracy: 0.4405

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02792980708181858
Inter Cos: 0.06281572580337524
Norm Quadratic Average: 32.321319580078125
Nearest Class Center Accuracy: 0.4745

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03320595994591713
Inter Cos: 0.07545403391122818
Norm Quadratic Average: 20.393096923828125
Nearest Class Center Accuracy: 0.4985

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.037319839000701904
Inter Cos: 0.0720682218670845
Norm Quadratic Average: 14.324204444885254
Nearest Class Center Accuracy: 0.589

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.46818542480469
Linear Weight Rank: 4031
Intra Cos: 0.0748547911643982
Inter Cos: 0.12248598039150238
Norm Quadratic Average: 77.99820709228516
Nearest Class Center Accuracy: 0.6165

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.30665397644043
Linear Weight Rank: 3671
Intra Cos: 0.15670450031757355
Inter Cos: 0.2465277910232544
Norm Quadratic Average: 35.29500961303711
Nearest Class Center Accuracy: 0.6

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.027357578277588
Linear Weight Rank: 10
Intra Cos: 0.2221338152885437
Inter Cos: 0.3589099049568176
Norm Quadratic Average: 22.32952880859375
Nearest Class Center Accuracy: 0.594

Output Layer:
Intra Cos: 0.27381598949432373
Inter Cos: 0.4708319306373596
Norm Quadratic Average: 13.839041709899902
Nearest Class Center Accuracy: 0.5895

