Model save path: ./New_Models/bn_True_dataset_CIFAR100_epochs_200_lr_0.01_model_type_vgg11_rand_seed_979323_test_samples_None_train_samples_None_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: 0.022893190383911133
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: 0.02411871962249279
Inter Cos: 0.02977822907269001
Norm Quadratic Average: 4.836572170257568
Nearest Class Center Accuracy: 0.04822

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021532803773880005
Inter Cos: 0.025510111823678017
Norm Quadratic Average: 2.507241725921631
Nearest Class Center Accuracy: 0.0604

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018653664737939835
Inter Cos: 0.017258888110518456
Norm Quadratic Average: 1.730211615562439
Nearest Class Center Accuracy: 0.0704

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026323627680540085
Inter Cos: 0.021580742672085762
Norm Quadratic Average: 1.1808422803878784
Nearest Class Center Accuracy: 0.08208

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03807542845606804
Inter Cos: 0.030368322506546974
Norm Quadratic Average: 0.8931199908256531
Nearest Class Center Accuracy: 0.09096

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.17343157529830933
Inter Cos: 0.11105553805828094
Norm Quadratic Average: 0.7070668935775757
Nearest Class Center Accuracy: 0.0991

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.6987991333007812
Inter Cos: 0.25254207849502563
Norm Quadratic Average: 1.0151689052581787
Nearest Class Center Accuracy: 0.1

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 3.924665689468384
Linear Weight Rank: 226
Intra Cos: 0.9259999394416809
Inter Cos: 0.38022497296333313
Norm Quadratic Average: 38.543888092041016
Nearest Class Center Accuracy: 0.1

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.944286823272705
Linear Weight Rank: 1907
Intra Cos: 0.9419708847999573
Inter Cos: 0.41239091753959656
Norm Quadratic Average: 32.64237594604492
Nearest Class Center Accuracy: 0.1

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 4.016364574432373
Linear Weight Rank: 95
Intra Cos: 0.944094717502594
Inter Cos: 0.42966920137405396
Norm Quadratic Average: 30.323806762695312
Nearest Class Center Accuracy: 0.1

Output Layer:
Intra Cos: 0.9486443996429443
Inter Cos: 0.44869810342788696
Norm Quadratic Average: 30.38737678527832
Nearest Class Center Accuracy: 0.1

Test Set:
Average Loss: 1.6178128124237061
Accuracy: 0.6079
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.18897390365600586, Weights: 0.016022419556975365
NC2 Equiangle: Features: 0.21463356711647727, Weights: 0.18646045415088383
NC3 Self-Duality: 0.14429797232151031
NC4 NCC Mismatch: 0.11750000000000005

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: 0.012051436118781567
Inter Cos: 0.24343031644821167
Norm Quadratic Average: 4.871796607971191
Nearest Class Center Accuracy: 0.2641

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.016226865351200104
Inter Cos: 0.2012285590171814
Norm Quadratic Average: 2.5259053707122803
Nearest Class Center Accuracy: 0.3985

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.013595887459814548
Inter Cos: 0.14095072448253632
Norm Quadratic Average: 1.7373610734939575
Nearest Class Center Accuracy: 0.5283

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.013468709774315357
Inter Cos: 0.15245485305786133
Norm Quadratic Average: 1.1829559803009033
Nearest Class Center Accuracy: 0.631

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.014328115619719028
Inter Cos: 0.15966852009296417
Norm Quadratic Average: 0.8856846690177917
Nearest Class Center Accuracy: 0.678

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05418163165450096
Inter Cos: 0.3663802444934845
Norm Quadratic Average: 0.6749727129936218
Nearest Class Center Accuracy: 0.6361

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1688595563173294
Inter Cos: 0.5552045702934265
Norm Quadratic Average: 0.8829024434089661
Nearest Class Center Accuracy: 0.6289

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 3.924665689468384
Linear Weight Rank: 226
Intra Cos: 0.246653214097023
Inter Cos: 0.625236988067627
Norm Quadratic Average: 31.840625762939453
Nearest Class Center Accuracy: 0.615

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.944286823272705
Linear Weight Rank: 1907
Intra Cos: 0.2574228048324585
Inter Cos: 0.6365917921066284
Norm Quadratic Average: 27.220029830932617
Nearest Class Center Accuracy: 0.6127

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 4.016364574432373
Linear Weight Rank: 95
Intra Cos: 0.2623174786567688
Inter Cos: 0.6366117596626282
Norm Quadratic Average: 25.498443603515625
Nearest Class Center Accuracy: 0.6087

Output Layer:
Intra Cos: 0.26670342683792114
Inter Cos: 0.6434012055397034
Norm Quadratic Average: 25.57253074645996
Nearest Class Center Accuracy: 0.605

