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Tune hyperparameters for kernel density estimation tutorial #774
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ernestum
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Sep 5, 2023
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LGTM and as already mentioned here, the pipeline could be fixed by specifying the seals version better in setup.py
AdamGleave
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Sep 5, 2023
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LGTM, 1 minor suggestion
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…patibleAI#774) * Pin huggingface_sb3 version. * Properly specify the compatible seals version so it does not auto-upgrade to 0.2. * Make random_mdp test deterministic by seeding the environment. * Tune hyperparameters for kernel density estimation tutorial * Modify .rst docs for density estimation to match tutorials * Update docs/algorithms/density.rst (nit) Co-authored-by: Adam Gleave <[email protected]> * Fix formatting in 7_train_density.ipynb and density.rst --------- Co-authored-by: Maximilian Ernestus <[email protected]> Co-authored-by: Adam Gleave <[email protected]>
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Description
This PR tunes parameters for the tutorial
7_train_density
. The new version (when flagFAST = False
) reaches better results in significantly lower number of PPO iterations:(results are mean +/- std from 10 random seeds)
To arrive at the hyperparameters, I performed a grid search, checking the following values:
Testing
Verified performance of the hyperparameters in a separate experiment, as well as ran the notebook itself.