Upload PPO Mountain Car agent trained for 10M steps with default hyperparameters
Browse files- README.md +37 -0
- config.json +1 -0
- ppo-MountainCar-v0.zip +3 -0
- ppo-MountainCar-v0/_stable_baselines3_version +1 -0
- ppo-MountainCar-v0/data +95 -0
- ppo-MountainCar-v0/policy.optimizer.pth +3 -0
- ppo-MountainCar-v0/policy.pth +3 -0
- ppo-MountainCar-v0/pytorch_variables.pth +3 -0
- ppo-MountainCar-v0/system_info.txt +7 -0
- results.json +1 -0
README.md
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---
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library_name: stable-baselines3
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tags:
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- MountainCar-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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- 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: MountainCar-v0
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type: MountainCar-v0
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metrics:
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- type: mean_reward
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value: -97.60 +/- 7.05
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name: mean_reward
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verified: false
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---
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# **PPO** Agent playing **MountainCar-v0**
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This is a trained model of a **PPO** agent playing **MountainCar-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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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 0x154206820>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x1542068b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x154206940>", 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ppo-MountainCar-v0.zip
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ppo-MountainCar-v0/_stable_baselines3_version
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ppo-MountainCar-v0/data
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oid sha256:0eeaf3fe5b5e00641ec06e4429f2e3cafa5e9341248324896332d7aa0b47408e
|
3 |
+
size 39937
|
ppo-MountainCar-v0/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
ppo-MountainCar-v0/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: macOS-13.2.1-arm64-arm-64bit Darwin Kernel Version 22.3.0: Mon Jan 30 20:39:35 PST 2023; root:xnu-8792.81.3~2/RELEASE_ARM64_T8103
|
2 |
+
- Python: 3.9.7
|
3 |
+
- Stable-Baselines3: 1.7.0
|
4 |
+
- PyTorch: 1.13.1
|
5 |
+
- GPU Enabled: False
|
6 |
+
- Numpy: 1.23.5
|
7 |
+
- Gym: 0.21.0
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": -97.6, "std_reward": 7.045565981523415, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-28T00:34:48.087097"}
|