1.	Start
2.	Initialise L2R, M, MBS, LR with default values
3.	for L2R in [0.0001, 0.0005, 0.001, 0.005]
4.	for M in [0.80, 0.85, 0.90, 0.95]
5.	for MBS in [4, 84, 16, 32, 64]
6.	for LR in [0.0001, 0.0005, 0.001, 0.005]
7.	model = CNN_train (train, L2R, M, MBS, LR)
8.	score = CNN_predict (test, model)
9.	cv_list.insert (score)
10.	scores_list.insert (mean(cv_list), L2R, M, MBS, LR)
11.	return max (scores_list)

L2R: ℓ₂ regularisation, M: Momentum, MBS: Mini‐batch size, LR: Learning rate

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