According to the implementation of other codes such as DGI, GRACE, etc., they all use the results of the last epoch or the minimum loss in the training process (early stopping) to calculate acc as the result. And your code is to calculate acc every 10 rounds, and use the best acc among all acc as your experimental result.
I think contrastive learning is unsupervised learning, and their codes are correct. It is unfair to compare the acc of your codes with them.
According to the implementation of other codes such as DGI, GRACE, etc., they all use the results of the last epoch or the minimum loss in the training process (early stopping) to calculate acc as the result. And your code is to calculate acc every 10 rounds, and use the best acc among all acc as your experimental result.
I think contrastive learning is unsupervised learning, and their codes are correct. It is unfair to compare the acc of your codes with them.