Model save path: ./New_Models/bn_False_dataset_CIFAR100_epochs_200_lr_0.01_model_type_vgg11_rand_seed_979323_test_samples_None_train_samples_None_weight_decay_0.005.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022893190383911133
Inter Cos: 0.07011394202709198
Norm Quadratic Average: 29.326318740844727
Nearest Class Center Accuracy: 0.03258

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04214300215244293
Inter Cos: 0.07155954837799072
Norm Quadratic Average: 37.47889709472656
Nearest Class Center Accuracy: 0.0423

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04454032704234123
Inter Cos: 0.06074530631303787
Norm Quadratic Average: 45.67771530151367
Nearest Class Center Accuracy: 0.04874

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0399351604282856
Inter Cos: 0.04482651501893997
Norm Quadratic Average: 64.02603149414062
Nearest Class Center Accuracy: 0.05662

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0357399545609951
Inter Cos: 0.038693275302648544
Norm Quadratic Average: 23.516935348510742
Nearest Class Center Accuracy: 0.06794

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.049962639808654785
Inter Cos: 0.044264793395996094
Norm Quadratic Average: 4.892210006713867
Nearest Class Center Accuracy: 0.0718

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.31179511547088623
Inter Cos: 0.27396824955940247
Norm Quadratic Average: 1.2887110710144043
Nearest Class Center Accuracy: 0.08304

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.6208147406578064
Inter Cos: 0.44886618852615356
Norm Quadratic Average: 1.9059761762619019
Nearest Class Center Accuracy: 0.0967

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 4.866724014282227
Linear Weight Rank: 182
Intra Cos: 0.7830851674079895
Inter Cos: 0.5399090051651001
Norm Quadratic Average: 20.748661041259766
Nearest Class Center Accuracy: 0.09972

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 4.947196960449219
Linear Weight Rank: 2912
Intra Cos: 0.8378647565841675
Inter Cos: 0.5699502229690552
Norm Quadratic Average: 33.91972732543945
Nearest Class Center Accuracy: 0.09998

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 5.026255130767822
Linear Weight Rank: 97
Intra Cos: 0.835193395614624
Inter Cos: 0.5383749604225159
Norm Quadratic Average: 46.293453216552734
Nearest Class Center Accuracy: 0.1

Output Layer:
Intra Cos: 0.8693466186523438
Inter Cos: 0.5978274345397949
Norm Quadratic Average: 65.80117797851562
Nearest Class Center Accuracy: 0.1

Test Set:
Average Loss: 3.6048257698059083
Accuracy: 0.4085
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.27929750084877014, Weights: 0.05696342512965202
NC2 Equiangle: Features: 0.2986447975852273, Weights: 0.1950372252801452
NC3 Self-Duality: 0.39742717146873474
NC4 NCC Mismatch: 0.3134

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.006621268577873707
Inter Cos: 0.4067547619342804
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: 0.014565388672053814
Inter Cos: 0.3005842864513397
Norm Quadratic Average: 37.644954681396484
Nearest Class Center Accuracy: 0.1893

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02042997255921364
Inter Cos: 0.3516250550746918
Norm Quadratic Average: 45.89923858642578
Nearest Class Center Accuracy: 0.2413

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.020851541310548782
Inter Cos: 0.37463340163230896
Norm Quadratic Average: 64.42507934570312
Nearest Class Center Accuracy: 0.2981

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025560401380062103
Inter Cos: 0.28522229194641113
Norm Quadratic Average: 23.73438262939453
Nearest Class Center Accuracy: 0.4262

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027192607522010803
Inter Cos: 0.33788806200027466
Norm Quadratic Average: 4.925838470458984
Nearest Class Center Accuracy: 0.4655

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.053128745406866074
Inter Cos: 0.6521527171134949
Norm Quadratic Average: 1.2799204587936401
Nearest Class Center Accuracy: 0.3315

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05342773720622063
Inter Cos: 0.6657995581626892
Norm Quadratic Average: 1.848932147026062
Nearest Class Center Accuracy: 0.3404

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 4.866724014282227
Linear Weight Rank: 182
Intra Cos: 0.06529535353183746
Inter Cos: 0.7062324285507202
Norm Quadratic Average: 19.86674690246582
Nearest Class Center Accuracy: 0.3832

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 4.947196960449219
Linear Weight Rank: 2912
Intra Cos: 0.06641992926597595
Inter Cos: 0.7072069048881531
Norm Quadratic Average: 32.29928207397461
Nearest Class Center Accuracy: 0.3978

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 5.026255130767822
Linear Weight Rank: 97
Intra Cos: 0.07857916504144669
Inter Cos: 0.677916944026947
Norm Quadratic Average: 44.34136962890625
Nearest Class Center Accuracy: 0.4019

Output Layer:
Intra Cos: 0.06686292588710785
Inter Cos: 0.7155084609985352
Norm Quadratic Average: 62.844390869140625
Nearest Class Center Accuracy: 0.4023

