Initial commit

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,69 @@
+---
+library_name: stable-baselines3
+tags:
+- Ant-v3
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: A2C
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: Ant-v3
+      type: Ant-v3
+    metrics:
+    - type: mean_reward
+      value: -182.48 +/- 159.86
+      name: mean_reward
+      verified: false
+---
+
+# **A2C** Agent playing **Ant-v3**
+This is a trained model of a **A2C** agent playing **Ant-v3**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
+and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
+
+The RL Zoo is a training framework for Stable Baselines3
+reinforcement learning agents,
+with hyperparameter optimization and pre-trained agents included.
+
+## Usage (with SB3 RL Zoo)
+
+RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
+SB3: https://github.com/DLR-RM/stable-baselines3<br/>
+SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
+
+Install the RL Zoo (with SB3 and SB3-Contrib):
+```bash
+pip install rl_zoo3
+```
+
+```
+# Download model and save it into the logs/ folder
+python -m rl_zoo3.load_from_hub --algo a2c --env Ant-v3 -orga qgallouedec -f logs/
+python -m rl_zoo3.enjoy --algo a2c --env Ant-v3  -f logs/
+```
+
+If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
+```
+python -m rl_zoo3.load_from_hub --algo a2c --env Ant-v3 -orga qgallouedec -f logs/
+python -m rl_zoo3.enjoy --algo a2c --env Ant-v3  -f logs/
+```
+
+## Training (with the RL Zoo)
+```
+python -m rl_zoo3.train --algo a2c --env Ant-v3 -f logs/
+# Upload the model and generate video (when possible)
+python -m rl_zoo3.push_to_hub --algo a2c --env Ant-v3 -f logs/ -orga qgallouedec
+```
+
+## Hyperparameters
+```python
+OrderedDict([('n_timesteps', 1000000.0),
+             ('normalize', True),
+             ('policy', 'MlpPolicy'),
+             ('normalize_kwargs', {'norm_obs': True, 'norm_reward': False})])
+```

a2c-Ant-v3.zip

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+oid sha256:1d5da71b568c0fe483645765b7f68a0fda8f545dcd7253f82c6e6f8e19a4d0f5
+size 219017

a2c-Ant-v3/_stable_baselines3_version

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+1.8.0a6

a2c-Ant-v3/data

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+- Python: 3.9.12
+- Stable-Baselines3: 1.8.0a6
+- PyTorch: 1.13.1+cu117
+- GPU Enabled: True
+- Numpy: 1.24.1
+- Gym: 0.21.0

args.yml

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+    - auto
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+  - - verbose
+    - 1
+  - - wandb_entity
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+  - - wandb_project_name
+    - sb3
+  - - wandb_tags
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+  - - yaml_file
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config.yml

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