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Hi, I was checking your lamb implementation and I think there is a mistake in it.
According to the paper, exp_avg and exp_avg_sq (m and v) must be updated this way:
m /= (1 - betta_1t)
v /= (1 - betta_2t)
In your implementation they are not updated and so even if self.debias==True, there is still update missing from adam_norm.
Please correct me if I'm wrong
The text was updated successfully, but these errors were encountered:
Hi, I was checking your lamb implementation and I think there is a mistake in it.
According to the paper, exp_avg and exp_avg_sq (m and v) must be updated this way:
m /= (1 - betta_1t)
v /= (1 - betta_2t)
In your implementation they are not updated and so even if self.debias==True, there is still update missing from adam_norm.
Please correct me if I'm wrong
The text was updated successfully, but these errors were encountered: