adhisetiawan
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0e5a401
second experiment with PPO model: more epoch, ent_coef tune
Browse files- README.md +1 -1
- config.json +1 -1
- ppo_LunarLander-v2-rev2.zip +3 -0
- ppo_LunarLander-v2-rev2/_stable_baselines3_version +1 -0
- ppo_LunarLander-v2-rev2/data +95 -0
- ppo_LunarLander-v2-rev2/policy.optimizer.pth +3 -0
- ppo_LunarLander-v2-rev2/policy.pth +3 -0
- ppo_LunarLander-v2-rev2/pytorch_variables.pth +3 -0
- ppo_LunarLander-v2-rev2/system_info.txt +7 -0
- replay.mp4 +0 -0
- results.json +1 -1
README.md
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type: LunarLander-v2
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metrics:
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- type: mean_reward
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value:
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name: mean_reward
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verified: false
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---
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type: LunarLander-v2
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metrics:
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- type: mean_reward
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value: 287.95 +/- 13.15
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name: mean_reward
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verified: false
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---
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config.json
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It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7f13033ff040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f13033ff0d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f13033ff160>", 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ppo_LunarLander-v2-rev2/policy.pth
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:e9dea37308cfdf332c63d339a31f7f21007e30ba2c2ebfef2c5503a013bca27f
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size 43393
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ppo_LunarLander-v2-rev2/pytorch_variables.pth
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@@ -0,0 +1,3 @@
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+
version https://git-lfs.github.com/spec/v1
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oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
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size 431
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ppo_LunarLander-v2-rev2/system_info.txt
ADDED
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- OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
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- Python: 3.8.10
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- Stable-Baselines3: 1.7.0
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+
- PyTorch: 1.13.1+cu116
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- GPU Enabled: True
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- Numpy: 1.22.4
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+
- Gym: 0.21.0
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replay.mp4
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
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results.json
CHANGED
@@ -1 +1 @@
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-
{"mean_reward":
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+
{"mean_reward": 287.9519646707384, "std_reward": 13.15137201899529, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-23T12:49:43.848258"}
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