removed irrelevant files. added license information

CKA/.gitignore

-.ipynb_checkpoints
-MNIST/*
-*.PNG.*
-*.PNG

CKA/results/20240620_cka_values.txt

-{'model1_name': 'BetterCNN', 'model2_name': 'SimpleCNN', 
-'CKA': tensor([
-        [0.9867, 0.6610, 0.4423],
-        [0.9191, 0.7801, 0.5646],
-        [0.6281, 0.9158, 0.7864],
-        [0.4664, 0.8383, 0.8708],
-        [0.4383, 0.7840, 0.8741]])
-		
-		, 'model1_layers': ['conv1', 'conv2', 'fc1', 'fc2', 'fc3'], 
-		'model2_layers': ['conv1', 'fc1', 'fc2'], 'dataset1_name': 'Dataset MNIST', 'dataset2_name': 'Dataset MNIST'}
-		
-{'model1_name': 'BetterCNN', 'model2_name': 'BetterCNN_no_dropout', 'CKA': tensor([[0.9978, 0.9478, 0.6513, 0.4629, 0.4117],
-        [0.9355, 0.9891, 0.7902, 0.5761, 0.5297],
-        [0.6247, 0.7293, 0.9578, 0.8131, 0.7348],
-        [0.4682, 0.5615, 0.8131, 0.9138, 0.8599],
-        [0.4380, 0.5257, 0.7401, 0.8632, 0.9353]]), 'model1_layers': ['conv1', 'conv2', 'fc1', 'fc2', 'fc3'], 'model2_layers': ['conv1', 'conv2', 'fc1', 'fc2', 'fc3'], 'dataset1_name': 'Dataset MNIST', 'dataset2_name': 'Dataset MNIST'}
\ No newline at end of file

CKA/results/CKA_values.txt

-simple_dropout_NOaugment_VS_simple_dropout_augment
-tensor([[0.9745, 0.8928, 0.5040],
-        [0.6511, 0.6861, 0.4116],
-        [0.4324, 0.4613, 0.2697]])
-simple_NOdropout_NOaugment_VS_simple_NOdropout_augment
-tensor([[0.9799, 0.9144, 0.4900],
-        [0.8961, 0.8515, 0.4447],
-        [0.5191, 0.4954, 0.2352]])
-better_dropout_NOaugment_VS_better_dropout_augment
-tensor([[0.9981, 0.9482, 0.8197, 0.7361, 0.5619],
-        [0.9586, 0.9740, 0.9025, 0.8273, 0.6336],
-        [0.8140, 0.8792, 0.9039, 0.8235, 0.6341],
-        [0.7199, 0.7659, 0.8067, 0.7586, 0.6172],
-        [0.4610, 0.4955, 0.5106, 0.4828, 0.4507]])
-better_NOdropout_NOaugment_VS_better_NOdropout_augment
-tensor([[0.9874, 0.9562, 0.8382, 0.7171, 0.5378],
-        [0.9415, 0.9345, 0.8716, 0.7609, 0.5597],
-        [0.7703, 0.7795, 0.8042, 0.7306, 0.5147],
-        [0.6582, 0.6721, 0.7075, 0.6481, 0.4224],
-        [0.5217, 0.5432, 0.5830, 0.5254, 0.3145]])
-simple_dropout_augment_VS_better_dropout_augment
-tensor([[0.9928, 0.9635, 0.8496, 0.7687, 0.5850],
-        [0.9019, 0.8740, 0.7889, 0.7053, 0.5242],
-        [0.5075, 0.4746, 0.4235, 0.3611, 0.2007]])
-simple_NOdropout_augment_VS_better_dropout_augment
-tensor([[0.9891, 0.9321, 0.8099, 0.7301, 0.5569],
-        [0.9138, 0.8944, 0.8150, 0.7406, 0.5789],
-        [0.4780, 0.4825, 0.4684, 0.4185, 0.3570]])
-simple_dropout_NOaugment_VS_simple_dropout_augment
-tensor([[0.9937, 0.7063, 0.3905],
-        [0.6679, 0.8717, 0.6766],
-        [0.4441, 0.7035, 0.6964]])
-simple_dropout_NOaugment_VS_simple_NOdropout_augment
-tensor([[0.9954, 0.6955, 0.3899],
-        [0.6554, 0.8835, 0.6585],
-        [0.4365, 0.7423, 0.6789]])
-better_dropout_NOaugment_VS_better_dropout_augment
-tensor([[0.9973, 0.8950, 0.5863, 0.4477, 0.4113],
-        [0.9348, 0.9519, 0.6882, 0.5378, 0.5062],
-        [0.6463, 0.8140, 0.9132, 0.7718, 0.7080],
-        [0.4816, 0.6226, 0.7541, 0.7713, 0.7211],
-        [0.4465, 0.5940, 0.7188, 0.7699, 0.7942]])
-better_dropout_NOaugment_VS_better_NOdropout_augment
-tensor([[0.9884, 0.8743, 0.6390, 0.4578, 0.4329],
-        [0.9247, 0.9243, 0.7341, 0.5337, 0.5236],
-        [0.6759, 0.8324, 0.9157, 0.7652, 0.7326],
-        [0.4953, 0.6296, 0.7335, 0.7204, 0.7155],
-        [0.4591, 0.6024, 0.7180, 0.6970, 0.7629]])
-simple_dropout_augment_VS_better_dropout_augment
-tensor([[0.9748, 0.8876, 0.6274, 0.4705, 0.4304],
-        [0.6711, 0.8077, 0.8871, 0.7797, 0.7037],
-        [0.3756, 0.5147, 0.7088, 0.8665, 0.8761]])
-simple_NOdropout_augment_VS_better_dropout_augment
-tensor([[0.9879, 0.8931, 0.6082, 0.4584, 0.4220],
-        [0.6628, 0.8166, 0.9036, 0.7895, 0.7176],
-        [0.3724, 0.5170, 0.7077, 0.8486, 0.8742]])