Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_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: 0.021450400352478027
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: 0.024009380489587784
Inter Cos: 0.09628400206565857
Norm Quadratic Average: 34.015689849853516
Nearest Class Center Accuracy: 0.2985

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029306653887033463
Inter Cos: 0.10506533831357956
Norm Quadratic Average: 28.022743225097656
Nearest Class Center Accuracy: 0.356625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03646174445748329
Inter Cos: 0.11375664919614792
Norm Quadratic Average: 30.41469955444336
Nearest Class Center Accuracy: 0.409625

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.053828164935112
Inter Cos: 0.14687059819698334
Norm Quadratic Average: 17.356430053710938
Nearest Class Center Accuracy: 0.4395

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06631442159414291
Inter Cos: 0.16199620068073273
Norm Quadratic Average: 12.386195182800293
Nearest Class Center Accuracy: 0.46975

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08727646619081497
Inter Cos: 0.16664497554302216
Norm Quadratic Average: 5.220224857330322
Nearest Class Center Accuracy: 0.527375

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.14385239779949188
Inter Cos: 0.2008686363697052
Norm Quadratic Average: 3.0868442058563232
Nearest Class Center Accuracy: 0.736875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.78327560424805
Linear Weight Rank: 4031
Intra Cos: 0.4431583881378174
Inter Cos: 0.39229077100753784
Norm Quadratic Average: 14.108011245727539
Nearest Class Center Accuracy: 0.962

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.4814453125
Linear Weight Rank: 3670
Intra Cos: 0.6662601232528687
Inter Cos: 0.5387428402900696
Norm Quadratic Average: 14.864289283752441
Nearest Class Center Accuracy: 0.99425

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.9982805252075195
Linear Weight Rank: 10
Intra Cos: 0.7346020936965942
Inter Cos: 0.6242530941963196
Norm Quadratic Average: 18.187576293945312
Nearest Class Center Accuracy: 0.996625

Output Layer:
Intra Cos: 0.8087647557258606
Inter Cos: 0.7585274577140808
Norm Quadratic Average: 23.81561851501465
Nearest Class Center Accuracy: 0.9955

Test Set:
Average Loss: 2.0746403427124025
Accuracy: 0.581
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.24709376692771912, Weights: 0.06277304142713547
NC2 Equiangle: Features: 0.4501472473144531, Weights: 0.22264186011420356
NC3 Self-Duality: 0.33989331126213074
NC4 NCC Mismatch: 0.1725

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
Inter Cos: 0.09352367371320724
Norm Quadratic Average: 27.53066635131836
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02510490082204342
Inter Cos: 0.07916312664747238
Norm Quadratic Average: 33.76424026489258
Nearest Class Center Accuracy: 0.3085

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032544877380132675
Inter Cos: 0.0899629294872284
Norm Quadratic Average: 27.853740692138672
Nearest Class Center Accuracy: 0.3675

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03808964788913727
Inter Cos: 0.10071831941604614
Norm Quadratic Average: 30.29905128479004
Nearest Class Center Accuracy: 0.431

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0529535673558712
Inter Cos: 0.13049165904521942
Norm Quadratic Average: 17.30942726135254
Nearest Class Center Accuracy: 0.4475

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06285928189754486
Inter Cos: 0.14394091069698334
Norm Quadratic Average: 12.380330085754395
Nearest Class Center Accuracy: 0.4665

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0736585408449173
Inter Cos: 0.14414091408252716
Norm Quadratic Average: 5.207988262176514
Nearest Class Center Accuracy: 0.4945

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0973438024520874
Inter Cos: 0.1743139922618866
Norm Quadratic Average: 3.054128885269165
Nearest Class Center Accuracy: 0.5225

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.78327560424805
Linear Weight Rank: 4031
Intra Cos: 0.20892147719860077
Inter Cos: 0.32756417989730835
Norm Quadratic Average: 13.463753700256348
Nearest Class Center Accuracy: 0.571

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.4814453125
Linear Weight Rank: 3670
Intra Cos: 0.2753255367279053
Inter Cos: 0.43544939160346985
Norm Quadratic Average: 13.904589653015137
Nearest Class Center Accuracy: 0.5735

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.9982805252075195
Linear Weight Rank: 10
Intra Cos: 0.2847074568271637
Inter Cos: 0.49720385670661926
Norm Quadratic Average: 16.965665817260742
Nearest Class Center Accuracy: 0.5695

Output Layer:
Intra Cos: 0.30332067608833313
Inter Cos: 0.5937556624412537
Norm Quadratic Average: 22.07067108154297
Nearest Class Center Accuracy: 0.547

