Al020198zee
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Test
Browse files- README.md +36 -0
- config.json +1 -0
- ppo-Walker2DBulletEnv-v0.zip +3 -0
- ppo-Walker2DBulletEnv-v0/_stable_baselines3_version +1 -0
- ppo-Walker2DBulletEnv-v0/data +120 -0
- ppo-Walker2DBulletEnv-v0/policy.optimizer.pth +3 -0
- ppo-Walker2DBulletEnv-v0/policy.pth +3 -0
- ppo-Walker2DBulletEnv-v0/pytorch_variables.pth +3 -0
- ppo-Walker2DBulletEnv-v0/system_info.txt +7 -0
- replay.mp4 +0 -0
- results.json +1 -0
- vec_normalize.pkl +3 -0
README.md
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---
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library_name: stable-baselines3
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tags:
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- Walker2DBulletEnv-v0
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- deep-reinforcement-learning
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- reinforcement-learning
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- stable-baselines3
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model-index:
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- name: PPO
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results:
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- metrics:
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- type: mean_reward
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value: 86.19 +/- 62.44
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name: mean_reward
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task:
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name: Walker2DBulletEnv-v0
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type: Walker2DBulletEnv-v0
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---
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# **PPO** Agent playing **Walker2DBulletEnv-v0**
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This is a trained model of a **PPO** agent playing **Walker2DBulletEnv-v0**
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using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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## Usage (with Stable-baselines3)
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TODO: Add your code
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```python
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from stable_baselines3 import ...
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from huggingface_sb3 import load_from_hub
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...
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```
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config.json
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If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). 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 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 0x7f5dd8545ef0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5dd8545f80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5dd854d050>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5dd854d0e0>", "_build": "<function 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"normalize_advantage": true,
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"target_kl": null
|
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}
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ppo-Walker2DBulletEnv-v0/policy.optimizer.pth
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:d3e23a937a64507087bba2c460b365bad30a51a9288bbb7f8b78bb73f0a71e20
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size 1183472
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ppo-Walker2DBulletEnv-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:4e3433a8af0bb8163dac2b2062288ccd99c96d0230ac296b7b4427f7013eb33f
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size 590974
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ppo-Walker2DBulletEnv-v0/pytorch_variables.pth
ADDED
@@ -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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ppo-Walker2DBulletEnv-v0/system_info.txt
ADDED
@@ -0,0 +1,7 @@
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OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
|
2 |
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Python: 3.7.13
|
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Stable-Baselines3: 1.6.0
|
4 |
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PyTorch: 1.12.0+cu113
|
5 |
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GPU Enabled: False
|
6 |
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Numpy: 1.21.6
|
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Gym: 0.21.0
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replay.mp4
ADDED
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results.json
ADDED
@@ -0,0 +1 @@
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|
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{"mean_reward": 86.18994121553843, "std_reward": 62.444648885496775, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-07-21T11:49:13.202592"}
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vec_normalize.pkl
ADDED
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version https://git-lfs.github.com/spec/v1
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size 3595
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