Model save path: ./New_Models/bn_False_dataset_CIFAR100_epochs_200_lr_0.01_model_type_vgg11_rand_seed_314159_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: 0.022893192246556282
Inter Cos: 0.07011394202709198
Norm Quadratic Average: 29.326322555541992
Nearest Class Center Accuracy: 0.03258

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036925528198480606
Inter Cos: 0.0478646345436573
Norm Quadratic Average: 36.159263610839844
Nearest Class Center Accuracy: 0.04518

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04075544327497482
Inter Cos: 0.03431795910000801
Norm Quadratic Average: 45.05070495605469
Nearest Class Center Accuracy: 0.05392

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03430759906768799
Inter Cos: 0.034126393496990204
Norm Quadratic Average: 71.46585845947266
Nearest Class Center Accuracy: 0.06378

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03588125482201576
Inter Cos: 0.03100932203233242
Norm Quadratic Average: 45.85894775390625
Nearest Class Center Accuracy: 0.07174

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036530524492263794
Inter Cos: 0.030956000089645386
Norm Quadratic Average: 32.21839141845703
Nearest Class Center Accuracy: 0.07556

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07093765586614609
Inter Cos: 0.04496852308511734
Norm Quadratic Average: 12.270198822021484
Nearest Class Center Accuracy: 0.08764

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.23912081122398376
Inter Cos: 0.13235445320606232
Norm Quadratic Average: 7.193600654602051
Nearest Class Center Accuracy: 0.0989

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 39.202083587646484
Linear Weight Rank: 4031
Intra Cos: 0.5897212028503418
Inter Cos: 0.25732332468032837
Norm Quadratic Average: 33.419891357421875
Nearest Class Center Accuracy: 0.1

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 18.055082321166992
Linear Weight Rank: 3662
Intra Cos: 0.6790528893470764
Inter Cos: 0.27627241611480713
Norm Quadratic Average: 35.75627899169922
Nearest Class Center Accuracy: 0.1

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 9.182252883911133
Linear Weight Rank: 98
Intra Cos: 0.7008905410766602
Inter Cos: 0.28727954626083374
Norm Quadratic Average: 42.69697189331055
Nearest Class Center Accuracy: 0.1

Output Layer:
Intra Cos: 0.7349634766578674
Inter Cos: 0.38103166222572327
Norm Quadratic Average: 71.18595886230469
Nearest Class Center Accuracy: 0.1

Test Set:
Average Loss: 4.117981481170654
Accuracy: 0.4817
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.23304103314876556, Weights: 0.033857230097055435
NC2 Equiangle: Features: 0.22097463896780303, Weights: 0.10600978042140151
NC3 Self-Duality: 0.5112743377685547
NC4 NCC Mismatch: 0.22540000000000004

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.006621268577873707
Inter Cos: 0.4067547917366028
Norm Quadratic Average: 29.42218780517578
Nearest Class Center Accuracy: 0.1136

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.016474980860948563
Inter Cos: 0.2844090759754181
Norm Quadratic Average: 36.37188720703125
Nearest Class Center Accuracy: 0.2318

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02360430732369423
Inter Cos: 0.2955142557621002
Norm Quadratic Average: 45.34669876098633
Nearest Class Center Accuracy: 0.2984

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02345775067806244
Inter Cos: 0.2468213438987732
Norm Quadratic Average: 71.97271728515625
Nearest Class Center Accuracy: 0.3754

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022488996386528015
Inter Cos: 0.21851089596748352
Norm Quadratic Average: 46.23716735839844
Nearest Class Center Accuracy: 0.4585

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019633546471595764
Inter Cos: 0.16249437630176544
Norm Quadratic Average: 32.36870193481445
Nearest Class Center Accuracy: 0.5044

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025694895535707474
Inter Cos: 0.20940563082695007
Norm Quadratic Average: 12.169233322143555
Nearest Class Center Accuracy: 0.5136

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05815890058875084
Inter Cos: 0.38698890805244446
Norm Quadratic Average: 6.967613697052002
Nearest Class Center Accuracy: 0.5064

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 39.202083587646484
Linear Weight Rank: 4031
Intra Cos: 0.11409589648246765
Inter Cos: 0.5377983450889587
Norm Quadratic Average: 30.825515747070312
Nearest Class Center Accuracy: 0.4957

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 18.055082321166992
Linear Weight Rank: 3662
Intra Cos: 0.12701240181922913
Inter Cos: 0.557375967502594
Norm Quadratic Average: 32.750606536865234
Nearest Class Center Accuracy: 0.484

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 9.182252883911133
Linear Weight Rank: 98
Intra Cos: 0.12412799149751663
Inter Cos: 0.5827098488807678
Norm Quadratic Average: 39.33610916137695
Nearest Class Center Accuracy: 0.4785

Output Layer:
Intra Cos: 0.13019394874572754
Inter Cos: 0.6718632578849792
Norm Quadratic Average: 66.06668090820312
Nearest Class Center Accuracy: 0.461

