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We noticed a performance drop when we resumed training with OnPolicyRunner which applied empirical normalization in our env.
There is a gap between the black line and blue one.
Additionally, we found the model performance cannot increase without the empirical normalization (The green and orange ones).
Many thanks.
The text was updated successfully, but these errors were encountered:
When you resume training, typically the episodes are "terminated" randomly to encourage a diverse set of sample collection. Otherwise PPO can get stuck in a local minima.
Hi there,
We noticed a performance drop when we resumed training with OnPolicyRunner which applied empirical normalization in our env.
There is a gap between the black line and blue one.
Additionally, we found the model performance cannot increase without the empirical normalization (The green and orange ones).
Many thanks.
The text was updated successfully, but these errors were encountered: