Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_265358_test_samples_None_train_samples_None_weight_decay_0.0001.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01989092119038105
Inter Cos: 0.10477277636528015
Norm Quadratic Average: 27.59717559814453
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018999602645635605
Inter Cos: 0.07588102668523788
Norm Quadratic Average: 69.36595153808594
Nearest Class Center Accuracy: 0.40028

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019754579290747643
Inter Cos: 0.06056921184062958
Norm Quadratic Average: 40.26849365234375
Nearest Class Center Accuracy: 0.52508

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01649116538465023
Inter Cos: 0.04612189158797264
Norm Quadratic Average: 42.6466064453125
Nearest Class Center Accuracy: 0.59778

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022668486461043358
Inter Cos: 0.04081859439611435
Norm Quadratic Average: 29.492063522338867
Nearest Class Center Accuracy: 0.70536

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.037473343312740326
Inter Cos: 0.051540933549404144
Norm Quadratic Average: 33.724246978759766
Nearest Class Center Accuracy: 0.79114

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12021736055612564
Inter Cos: 0.11885672807693481
Norm Quadratic Average: 24.29386329650879
Nearest Class Center Accuracy: 0.91852

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3970811069011688
Inter Cos: 0.2223433554172516
Norm Quadratic Average: 19.097698211669922
Nearest Class Center Accuracy: 0.98316

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 73.61004638671875
Linear Weight Rank: 4031
Intra Cos: 0.7153112888336182
Inter Cos: 0.34251007437705994
Norm Quadratic Average: 103.25070190429688
Nearest Class Center Accuracy: 0.9673

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 30.55575942993164
Linear Weight Rank: 3669
Intra Cos: 0.9510423541069031
Inter Cos: 0.05397603660821915
Norm Quadratic Average: 73.18161010742188
Nearest Class Center Accuracy: 0.99426

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 4.032666206359863
Linear Weight Rank: 10
Intra Cos: 0.9330738186836243
Inter Cos: 0.01948469877243042
Norm Quadratic Average: 30.959911346435547
Nearest Class Center Accuracy: 0.99984

Output Layer:
Intra Cos: 0.9866124987602234
Inter Cos: 0.32003122568130493
Norm Quadratic Average: 22.58488655090332
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.1171750727653504
Accuracy: 0.8325
NC1 Within Class Collapse: 5.271925449371338
NC2 Equinorm: Features: 0.2805165946483612, Weights: 0.019276855513453484
NC2 Equiangle: Features: 0.09267847273084852, Weights: 0.12222790188259548
NC3 Self-Duality: 0.9460367560386658
NC4 NCC Mismatch: 0.09450000000000003

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526077270507812
Inter Cos: 0.1042705774307251
Norm Quadratic Average: 27.550134658813477
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0176694393157959
Inter Cos: 0.07745196670293808
Norm Quadratic Average: 69.31517791748047
Nearest Class Center Accuracy: 0.4171

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018469417467713356
Inter Cos: 0.061933476477861404
Norm Quadratic Average: 40.28338623046875
Nearest Class Center Accuracy: 0.5319

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.015305486507713795
Inter Cos: 0.0471305288374424
Norm Quadratic Average: 42.675750732421875
Nearest Class Center Accuracy: 0.6007

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01996675692498684
Inter Cos: 0.041937559843063354
Norm Quadratic Average: 29.504669189453125
Nearest Class Center Accuracy: 0.6767

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030527926981449127
Inter Cos: 0.0536370575428009
Norm Quadratic Average: 33.66722106933594
Nearest Class Center Accuracy: 0.7227

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0875856801867485
Inter Cos: 0.12433303892612457
Norm Quadratic Average: 24.13753890991211
Nearest Class Center Accuracy: 0.772

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.29600265622138977
Inter Cos: 0.2398703396320343
Norm Quadratic Average: 18.606016159057617
Nearest Class Center Accuracy: 0.8022

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 73.61004638671875
Linear Weight Rank: 4031
Intra Cos: 0.5269114375114441
Inter Cos: 0.4779529273509979
Norm Quadratic Average: 99.30816650390625
Nearest Class Center Accuracy: 0.775

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 30.55575942993164
Linear Weight Rank: 3669
Intra Cos: 0.5923993587493896
Inter Cos: 0.32159939408302307
Norm Quadratic Average: 66.30963897705078
Nearest Class Center Accuracy: 0.7806

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 4.032666206359863
Linear Weight Rank: 10
Intra Cos: 0.5326462388038635
Inter Cos: 0.23763103783130646
Norm Quadratic Average: 28.141633987426758
Nearest Class Center Accuracy: 0.7954

Output Layer:
Intra Cos: 0.6048073172569275
Inter Cos: 0.3403286933898926
Norm Quadratic Average: 20.186521530151367
Nearest Class Center Accuracy: 0.8246

