Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_weight_decay_0.0007.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: 0.11371058970689774
Norm Quadratic Average: 27.691617965698242
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025545483455061913
Inter Cos: 0.10939722508192062
Norm Quadratic Average: 29.35952377319336
Nearest Class Center Accuracy: 0.318375

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02801547758281231
Inter Cos: 0.11194274574518204
Norm Quadratic Average: 23.242990493774414
Nearest Class Center Accuracy: 0.3815

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03606022521853447
Inter Cos: 0.11682353913784027
Norm Quadratic Average: 28.189048767089844
Nearest Class Center Accuracy: 0.422

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05656890571117401
Inter Cos: 0.14962580800056458
Norm Quadratic Average: 17.981239318847656
Nearest Class Center Accuracy: 0.44675

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06998102366924286
Inter Cos: 0.15826886892318726
Norm Quadratic Average: 16.58415412902832
Nearest Class Center Accuracy: 0.475875

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09032826125621796
Inter Cos: 0.16478918492794037
Norm Quadratic Average: 9.107062339782715
Nearest Class Center Accuracy: 0.526625

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12061798572540283
Inter Cos: 0.1762489527463913
Norm Quadratic Average: 6.726667881011963
Nearest Class Center Accuracy: 0.698375

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.0556640625
Linear Weight Rank: 4031
Intra Cos: 0.3143549859523773
Inter Cos: 0.2626679837703705
Norm Quadratic Average: 26.797029495239258
Nearest Class Center Accuracy: 0.97325

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.687774658203125
Linear Weight Rank: 3670
Intra Cos: 0.5983224511146545
Inter Cos: 0.41342273354530334
Norm Quadratic Average: 23.429529190063477
Nearest Class Center Accuracy: 0.999

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2480263710021973
Linear Weight Rank: 10
Intra Cos: 0.7465814352035522
Inter Cos: 0.5200881958007812
Norm Quadratic Average: 27.66028594970703
Nearest Class Center Accuracy: 0.999625

Output Layer:
Intra Cos: 0.8122418522834778
Inter Cos: 0.669284462928772
Norm Quadratic Average: 33.922019958496094
Nearest Class Center Accuracy: 0.9965

Test Set:
Average Loss: 2.9422512130737304
Accuracy: 0.594
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.25457778573036194, Weights: 0.04701821133494377
NC2 Equiangle: Features: 0.41587295532226565, Weights: 0.1630970425075955
NC3 Self-Duality: 0.44438567757606506
NC4 NCC Mismatch: 0.14449999999999996

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352368116378784
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: 0.0251542367041111
Inter Cos: 0.09320244193077087
Norm Quadratic Average: 29.1770076751709
Nearest Class Center Accuracy: 0.336

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029091740027070045
Inter Cos: 0.09791731834411621
Norm Quadratic Average: 23.10017204284668
Nearest Class Center Accuracy: 0.396

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03601571545004845
Inter Cos: 0.10320328176021576
Norm Quadratic Average: 28.069561004638672
Nearest Class Center Accuracy: 0.449

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05276522785425186
Inter Cos: 0.13218151032924652
Norm Quadratic Average: 17.908540725708008
Nearest Class Center Accuracy: 0.4655

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06261765956878662
Inter Cos: 0.13856780529022217
Norm Quadratic Average: 16.53622817993164
Nearest Class Center Accuracy: 0.478

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07396706938743591
Inter Cos: 0.14194299280643463
Norm Quadratic Average: 9.06593132019043
Nearest Class Center Accuracy: 0.493

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08497713506221771
Inter Cos: 0.14877057075500488
Norm Quadratic Average: 6.6684675216674805
Nearest Class Center Accuracy: 0.5385

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.0556640625
Linear Weight Rank: 4031
Intra Cos: 0.1397845596075058
Inter Cos: 0.24267403781414032
Norm Quadratic Average: 25.879058837890625
Nearest Class Center Accuracy: 0.6055

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.687774658203125
Linear Weight Rank: 3670
Intra Cos: 0.2167324274778366
Inter Cos: 0.3689388930797577
Norm Quadratic Average: 21.998428344726562
Nearest Class Center Accuracy: 0.606

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2480263710021973
Linear Weight Rank: 10
Intra Cos: 0.2504066526889801
Inter Cos: 0.45620977878570557
Norm Quadratic Average: 25.726720809936523
Nearest Class Center Accuracy: 0.5965

Output Layer:
Intra Cos: 0.28661152720451355
Inter Cos: 0.5660824179649353
Norm Quadratic Average: 31.41792869567871
Nearest Class Center Accuracy: 0.5765

