Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_265358_test_samples_None_train_samples_None_weight_decay_0.03.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: 0.025612834841012955
Inter Cos: 0.10014466196298599
Norm Quadratic Average: 12.07995891571045
Nearest Class Center Accuracy: 0.3665

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03527338430285454
Inter Cos: 0.11895520240068436
Norm Quadratic Average: 3.4083757400512695
Nearest Class Center Accuracy: 0.46516

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08735331892967224
Inter Cos: 0.1987728625535965
Norm Quadratic Average: 1.206394076347351
Nearest Class Center Accuracy: 0.53376

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.14167329668998718
Inter Cos: 0.39276713132858276
Norm Quadratic Average: 0.7674341201782227
Nearest Class Center Accuracy: 0.53324

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.20180338621139526
Inter Cos: 0.5821720361709595
Norm Quadratic Average: 1.1119530200958252
Nearest Class Center Accuracy: 0.54908

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.23613403737545013
Inter Cos: 0.6427975296974182
Norm Quadratic Average: 1.4651700258255005
Nearest Class Center Accuracy: 0.55086

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.20996582508087158
Inter Cos: 0.6267740726470947
Norm Quadratic Average: 1.8815234899520874
Nearest Class Center Accuracy: 0.55608

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 1.6763486862182617
Linear Weight Rank: 3
Intra Cos: 0.22793403267860413
Inter Cos: 0.6546062231063843
Norm Quadratic Average: 12.436985969543457
Nearest Class Center Accuracy: 0.56432

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 1.6895699501037598
Linear Weight Rank: 2440
Intra Cos: 0.24603727459907532
Inter Cos: 0.6740249991416931
Norm Quadratic Average: 11.897648811340332
Nearest Class Center Accuracy: 0.5705

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.718288779258728
Linear Weight Rank: 9
Intra Cos: 0.2992636561393738
Inter Cos: 0.6797354221343994
Norm Quadratic Average: 9.794189453125
Nearest Class Center Accuracy: 0.5799

Output Layer:
Intra Cos: 0.41305580735206604
Inter Cos: 0.7889469861984253
Norm Quadratic Average: 8.329137802124023
Nearest Class Center Accuracy: 0.57462

Test Set:
Average Loss: 1.1431328596115111
Accuracy: 0.5728
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2566956877708435, Weights: 0.1758718192577362
NC2 Equiangle: Features: 0.5702532450358073, Weights: 0.31690584818522133
NC3 Self-Duality: 0.3122137188911438
NC4 NCC Mismatch: 0.23629999999999995

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: 0.022916436195373535
Inter Cos: 0.10070539265871048
Norm Quadratic Average: 12.074088096618652
Nearest Class Center Accuracy: 0.3809

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03392846882343292
Inter Cos: 0.12169469147920609
Norm Quadratic Average: 3.4097139835357666
Nearest Class Center Accuracy: 0.4735

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0832248404622078
Inter Cos: 0.2012864500284195
Norm Quadratic Average: 1.2084224224090576
Nearest Class Center Accuracy: 0.5328

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.13838495314121246
Inter Cos: 0.3961425721645355
Norm Quadratic Average: 0.7684730291366577
Nearest Class Center Accuracy: 0.5271

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.20170603692531586
Inter Cos: 0.5842909812927246
Norm Quadratic Average: 1.1127818822860718
Nearest Class Center Accuracy: 0.5396

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.23335421085357666
Inter Cos: 0.6420239210128784
Norm Quadratic Average: 1.4647003412246704
Nearest Class Center Accuracy: 0.5345

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2071073055267334
Inter Cos: 0.6245874762535095
Norm Quadratic Average: 1.8793054819107056
Nearest Class Center Accuracy: 0.5369

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 1.6763486862182617
Linear Weight Rank: 3
Intra Cos: 0.2258249819278717
Inter Cos: 0.6507658362388611
Norm Quadratic Average: 12.429976463317871
Nearest Class Center Accuracy: 0.5452

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 1.6895699501037598
Linear Weight Rank: 2440
Intra Cos: 0.24443775415420532
Inter Cos: 0.6684166789054871
Norm Quadratic Average: 11.89745044708252
Nearest Class Center Accuracy: 0.5517

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.718288779258728
Linear Weight Rank: 9
Intra Cos: 0.2931874990463257
Inter Cos: 0.6710505485534668
Norm Quadratic Average: 9.804569244384766
Nearest Class Center Accuracy: 0.5607

Output Layer:
Intra Cos: 0.40247172117233276
Inter Cos: 0.776427149772644
Norm Quadratic Average: 8.344130516052246
Nearest Class Center Accuracy: 0.5504

