Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_314159_weight_decay_0.03.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: 27.691621780395508
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028000356629490852
Inter Cos: 0.10222688317298889
Norm Quadratic Average: 14.414091110229492
Nearest Class Center Accuracy: 0.310125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03403997793793678
Inter Cos: 0.1261739283800125
Norm Quadratic Average: 6.537109851837158
Nearest Class Center Accuracy: 0.364375

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06524575501680374
Inter Cos: 0.19866251945495605
Norm Quadratic Average: 6.39730167388916
Nearest Class Center Accuracy: 0.4

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10867155343294144
Inter Cos: 0.3107043504714966
Norm Quadratic Average: 5.555479049682617
Nearest Class Center Accuracy: 0.380875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.16457413136959076
Inter Cos: 0.40337613224983215
Norm Quadratic Average: 6.48344612121582
Nearest Class Center Accuracy: 0.373375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.22504639625549316
Inter Cos: 0.48427560925483704
Norm Quadratic Average: 5.341611385345459
Nearest Class Center Accuracy: 0.376375

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.22859546542167664
Inter Cos: 0.5213571190834045
Norm Quadratic Average: 4.05964469909668
Nearest Class Center Accuracy: 0.39525

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.992473602294922
Linear Weight Rank: 4031
Intra Cos: 0.24102336168289185
Inter Cos: 0.5559960603713989
Norm Quadratic Average: 17.551488876342773
Nearest Class Center Accuracy: 0.4175

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.783462524414062
Linear Weight Rank: 3669
Intra Cos: 0.2580839991569519
Inter Cos: 0.590825617313385
Norm Quadratic Average: 11.227754592895508
Nearest Class Center Accuracy: 0.422

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.5417011976242065
Linear Weight Rank: 10
Intra Cos: 0.2896941006183624
Inter Cos: 0.6319305896759033
Norm Quadratic Average: 7.440894603729248
Nearest Class Center Accuracy: 0.42025

Output Layer:
Intra Cos: 0.3295239806175232
Inter Cos: 0.7053888440132141
Norm Quadratic Average: 5.851114273071289
Nearest Class Center Accuracy: 0.392375

Test Set:
Average Loss: 1.5033970108032226
Accuracy: 0.418
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2589277923107147, Weights: 0.09898369759321213
NC2 Equiangle: Features: 0.751765865749783, Weights: 0.28082947201199004
NC3 Self-Duality: 0.4091644585132599
NC4 NCC Mismatch: 0.269

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
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: 0.028041956946253777
Inter Cos: 0.09678679704666138
Norm Quadratic Average: 14.341768264770508
Nearest Class Center Accuracy: 0.331

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03727100044488907
Inter Cos: 0.10801348835229874
Norm Quadratic Average: 6.4826812744140625
Nearest Class Center Accuracy: 0.3735

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06353335082530975
Inter Cos: 0.18945996463298798
Norm Quadratic Average: 6.337515830993652
Nearest Class Center Accuracy: 0.415

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09736437350511551
Inter Cos: 0.3025463819503784
Norm Quadratic Average: 5.5135602951049805
Nearest Class Center Accuracy: 0.3945

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1454915851354599
Inter Cos: 0.39981719851493835
Norm Quadratic Average: 6.453032970428467
Nearest Class Center Accuracy: 0.366

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.19272172451019287
Inter Cos: 0.4849012792110443
Norm Quadratic Average: 5.328641414642334
Nearest Class Center Accuracy: 0.359

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.21659967303276062
Inter Cos: 0.5257292985916138
Norm Quadratic Average: 4.053955078125
Nearest Class Center Accuracy: 0.3875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.992473602294922
Linear Weight Rank: 4031
Intra Cos: 0.24421319365501404
Inter Cos: 0.5631994009017944
Norm Quadratic Average: 17.55406379699707
Nearest Class Center Accuracy: 0.408

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.783462524414062
Linear Weight Rank: 3669
Intra Cos: 0.27615123987197876
Inter Cos: 0.600994884967804
Norm Quadratic Average: 11.254012107849121
Nearest Class Center Accuracy: 0.423

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.5417011976242065
Linear Weight Rank: 10
Intra Cos: 0.31821098923683167
Inter Cos: 0.645724356174469
Norm Quadratic Average: 7.473196506500244
Nearest Class Center Accuracy: 0.4185

Output Layer:
Intra Cos: 0.38621699810028076
Inter Cos: 0.727952241897583
Norm Quadratic Average: 5.891359806060791
Nearest Class Center Accuracy: 0.3925

