Model save path: ./New_Models/bn_False_dataset_CIFAR100_epochs_200_lr_0.01_model_type_vgg19_rand_seed_265358_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: 0.022893192246556282
Inter Cos: 0.07011394202709198
Norm Quadratic Average: 29.326313018798828
Nearest Class Center Accuracy: 0.03258

Layer 1: Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.048152778297662735
Inter Cos: 0.057969581335783005
Norm Quadratic Average: 2.6547316320062186e-13
Nearest Class Center Accuracy: 0.03596

Layer 2: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 3: Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 4: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 5: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 6: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 7: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 8: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 2.0358238220214844
Inter Cos: 2.03375244140625
Norm Quadratic Average: 1.4973568266036865e-22
Nearest Class Center Accuracy: 0.01

Layer 9: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 10: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 11: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 4.641364574432373
Inter Cos: 4.634081840515137
Norm Quadratic Average: 2.117582368135751e-22
Nearest Class Center Accuracy: 0.01

Layer 12: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 2.9733898639678955
Inter Cos: 2.9694433212280273
Norm Quadratic Average: 1.4973568266036865e-22
Nearest Class Center Accuracy: 0.01

Layer 13: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 1.9638255834579468
Inter Cos: 1.9618985652923584
Norm Quadratic Average: 2.367529096313811e-22
Nearest Class Center Accuracy: 0.01

Layer 14: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 1.6182140111923218
Inter Cos: 1.6169779300689697
Norm Quadratic Average: 3.7433921296180887e-22
Nearest Class Center Accuracy: 0.01

Layer 15: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 1.2152985334396362
Inter Cos: 1.2148685455322266
Norm Quadratic Average: 6.308476482841739e-22
Nearest Class Center Accuracy: 0.01

Layer 16: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 6.723017325141467e-13
Linear Weight Rank: 4031
Intra Cos: 1.015474557876587
Inter Cos: 1.0154438018798828
Norm Quadratic Average: 4.5995002337002474e-21
Nearest Class Center Accuracy: 0.01

Layer 17: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.7168190115146873e-13
Linear Weight Rank: 3671
Intra Cos: 1.1359586715698242
Inter Cos: 1.1360595226287842
Norm Quadratic Average: 7.726274352125607e-22
Nearest Class Center Accuracy: 0.01

Layer 18: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 4.2372643615411557e-14
Linear Weight Rank: 99
Intra Cos: 1.0007258653640747
Inter Cos: 1.0007246732711792
Norm Quadratic Average: 2.3746210694477182e-21
Nearest Class Center Accuracy: 0.01

Output Layer:
Intra Cos: 0.9999997615814209
Inter Cos: 1.0000001192092896
Norm Quadratic Average: 4.8171977518052245e-09
Nearest Class Center Accuracy: 0.01

Test Set:
Average Loss: 4.605170426940918
Accuracy: 0.01
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 1.0586702823638916, Weights: 0.010884481482207775
NC2 Equiangle: Features: nan, Weights: 0.014872317843967014
NC3 Self-Duality: 4.3703155517578125
NC4 NCC Mismatch: 1.0

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.006621268577873707
Inter Cos: 0.4067547917366028
Norm Quadratic Average: 29.422183990478516
Nearest Class Center Accuracy: 0.1136

Layer 1: Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.012215212918817997
Inter Cos: 0.341356098651886
Norm Quadratic Average: 2.6606920334494577e-13
Nearest Class Center Accuracy: 0.1326

Layer 2: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 3: Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 4: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 5: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 6: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 7: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 8: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 9: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 10: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 11: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 12: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 13: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 14: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 15: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.01

Layer 16: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 6.723017325141467e-13
Linear Weight Rank: 4031
Intra Cos: 3.1782920360565186
Inter Cos: 3.156511068344116
Norm Quadratic Average: 5.590076381239578e-22
Nearest Class Center Accuracy: 0.01

Layer 17: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.7168190115146873e-13
Linear Weight Rank: 3671
Intra Cos: 21.722322463989258
Inter Cos: 21.51511573791504
Norm Quadratic Average: 3.743392066509216e-23
Nearest Class Center Accuracy: 0.01

Layer 18: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 4.2372643615411557e-14
Linear Weight Rank: 99
Intra Cos: 1.0311254262924194
Inter Cos: 1.030814528465271
Norm Quadratic Average: 4.251676036779884e-22
Nearest Class Center Accuracy: 0.01

Output Layer:
Intra Cos: 0.9999995827674866
Inter Cos: 1.000000238418579
Norm Quadratic Average: 1.0022285223953986e-09
Nearest Class Center Accuracy: 0.01

