masterdezign
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Initial commit
Browse files- .gitattributes +1 -0
- 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 +3 -0
- results.json +1 -0
- vec_normalize.pkl +0 -0
.gitattributes
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replay.mp4 filter=lfs diff=lfs merge=lfs -text
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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: 2286.76 +/- 22.80
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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 0x7f1d1282f3b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1d1282f440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1d1282f4d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1d1282f560>", "_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 sha256:0f5fd30923154380b7e82df7ce8589ba65d793bd920b069f83326e5718a9340f
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size 1183984
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ppo-Walker2DBulletEnv-v0/policy.pth
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:3015a75dabf352c6e9966c4b7f7bcb77459d14fe429a23c93d5c3119784a1951
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size 591102
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ppo-Walker2DBulletEnv-v0/pytorch_variables.pth
ADDED
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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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1 |
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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
|
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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 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
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version https://git-lfs.github.com/spec/v1
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size 1074557
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results.json
ADDED
@@ -0,0 +1 @@
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|
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{"mean_reward": 2286.7615762992764, "std_reward": 22.79866020721537, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-07-18T16:03:51.967472"}
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vec_normalize.pkl
ADDED
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