Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_314159_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: 0.01989092119038105
Inter Cos: 0.10477276146411896
Norm Quadratic Average: 27.59718132019043
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019067825749516487
Inter Cos: 0.07196880877017975
Norm Quadratic Average: 3.7475380897521973
Nearest Class Center Accuracy: 0.40692

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02076573483645916
Inter Cos: 0.05379091203212738
Norm Quadratic Average: 1.8114676475524902
Nearest Class Center Accuracy: 0.53924

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01660148985683918
Inter Cos: 0.04618482291698456
Norm Quadratic Average: 1.2906970977783203
Nearest Class Center Accuracy: 0.62572

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026180066168308258
Inter Cos: 0.044198207557201385
Norm Quadratic Average: 0.8684102892875671
Nearest Class Center Accuracy: 0.78396

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06660754233598709
Inter Cos: 0.07572406530380249
Norm Quadratic Average: 0.6176724433898926
Nearest Class Center Accuracy: 0.91368

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.38256847858428955
Inter Cos: 0.18813170492649078
Norm Quadratic Average: 0.41833800077438354
Nearest Class Center Accuracy: 0.99706

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.8768580555915833
Inter Cos: 0.06838144361972809
Norm Quadratic Average: 0.7689827084541321
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.1351542472839355
Linear Weight Rank: 33
Intra Cos: 0.985797107219696
Inter Cos: 0.004522738046944141
Norm Quadratic Average: 23.638370513916016
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.139258623123169
Linear Weight Rank: 1254
Intra Cos: 0.9915712475776672
Inter Cos: 0.047681666910648346
Norm Quadratic Average: 15.802471160888672
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.136772632598877
Linear Weight Rank: 9
Intra Cos: 0.9932361841201782
Inter Cos: 0.07632508873939514
Norm Quadratic Average: 10.76546573638916
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9941168427467346
Inter Cos: 0.1514868140220642
Norm Quadratic Average: 7.723986625671387
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.39311634368896486
Accuracy: 0.8807
NC1 Within Class Collapse: 2.7156639099121094
NC2 Equinorm: Features: 0.1169101893901825, Weights: 0.002754662884399295
NC2 Equiangle: Features: 0.11664246453179253, Weights: 0.025278907352023653
NC3 Self-Duality: 0.03433270752429962
NC4 NCC Mismatch: 0.011800000000000033

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526073545217514
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: 0.018014555796980858
Inter Cos: 0.07351585477590561
Norm Quadratic Average: 3.745121717453003
Nearest Class Center Accuracy: 0.4286

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01963142305612564
Inter Cos: 0.05477295443415642
Norm Quadratic Average: 1.8122631311416626
Nearest Class Center Accuracy: 0.5462

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.015596351586282253
Inter Cos: 0.04684946686029434
Norm Quadratic Average: 1.2920258045196533
Nearest Class Center Accuracy: 0.6288

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0223463736474514
Inter Cos: 0.044957369565963745
Norm Quadratic Average: 0.8679119348526001
Nearest Class Center Accuracy: 0.7416

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05131346732378006
Inter Cos: 0.07843831181526184
Norm Quadratic Average: 0.612238883972168
Nearest Class Center Accuracy: 0.8062

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.25943437218666077
Inter Cos: 0.2036389708518982
Norm Quadratic Average: 0.4042324721813202
Nearest Class Center Accuracy: 0.8556

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5182719826698303
Inter Cos: 0.24641084671020508
Norm Quadratic Average: 0.7053085565567017
Nearest Class Center Accuracy: 0.8767

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.1351542472839355
Linear Weight Rank: 33
Intra Cos: 0.6211151480674744
Inter Cos: 0.23221378028392792
Norm Quadratic Average: 21.013790130615234
Nearest Class Center Accuracy: 0.8776

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.139258623123169
Linear Weight Rank: 1254
Intra Cos: 0.6295894384384155
Inter Cos: 0.24713316559791565
Norm Quadratic Average: 14.037552833557129
Nearest Class Center Accuracy: 0.8777

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.136772632598877
Linear Weight Rank: 9
Intra Cos: 0.6368746161460876
Inter Cos: 0.2696775794029236
Norm Quadratic Average: 9.561775207519531
Nearest Class Center Accuracy: 0.8778

Output Layer:
Intra Cos: 0.6487775444984436
Inter Cos: 0.3112581968307495
Norm Quadratic Average: 6.877664566040039
Nearest Class Center Accuracy: 0.8782

