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README.md +37 -0
TQC-PandaPush-v3.zip +3 -0
TQC-PandaPush-v3/_stable_baselines3_version +1 -0
TQC-PandaPush-v3/actor.optimizer.pth +3 -0
TQC-PandaPush-v3/critic.optimizer.pth +3 -0
TQC-PandaPush-v3/data +125 -0
TQC-PandaPush-v3/ent_coef_optimizer.pth +3 -0
TQC-PandaPush-v3/policy.pth +3 -0
TQC-PandaPush-v3/pytorch_variables.pth +3 -0
TQC-PandaPush-v3/system_info.txt +9 -0
config.json +1 -0
replay.mp4 +0 -0
results.json +1 -0

README.md ADDED Viewed

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+---
+library_name: stable-baselines3
+tags:
+- PandaPush-v3
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: TQC
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: PandaPush-v3
+      type: PandaPush-v3
+    metrics:
+    - type: mean_reward
+      value: -45.00 +/- 15.00
+      name: mean_reward
+      verified: false
+---
+# **TQC** Agent playing **PandaPush-v3**
+This is a trained model of a **TQC** agent playing **PandaPush-v3**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+## Usage (with Stable-baselines3)
+TODO: Add your code
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+...
+```

TQC-PandaPush-v3.zip ADDED Viewed

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TQC-PandaPush-v3/_stable_baselines3_version ADDED Viewed

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1	+ 2.2.1

TQC-PandaPush-v3/actor.optimizer.pth ADDED Viewed

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TQC-PandaPush-v3/critic.optimizer.pth ADDED Viewed

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TQC-PandaPush-v3/data ADDED Viewed

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+        "__module__": "sb3_contrib.tqc.policies",
+        "__doc__": "\n    Policy class (with both actor and critic) for TQC.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` when using gSDE 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 clip_mean: Clip the mean output when using gSDE to avoid numerical instability.\n    :param features_extractor_class: Features extractor to use.\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    :param n_quantiles: Number of quantiles for the critic.\n    :param n_critics: Number of critic networks to create.\n    :param share_features_extractor: Whether to share or not the features extractor\n        between the actor and the critic (this saves computation time)\n    ",
+        "__init__": "<function MultiInputPolicy.__init__ at 0x7f675132b5b0>",
+        "__abstractmethods__": "frozenset()",
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+            512,
+            512
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+    "action_noise": null,
+    "start_time": 1704880180866482285,
+    "learning_rate": 0.001,
+    "tensorboard_log": "./TQC/logs",
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+    "_episode_num": 4894,
+    "use_sde": false,
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+    "_stats_window_size": 100,
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+    "batch_norm_stats_target": []
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+- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.2.1
+- PyTorch: 2.1.0+cu121
+- GPU Enabled: False
+- Numpy: 1.23.5
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.29.1
+- OpenAI Gym: 0.25.2

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