Initial commit

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- FetchPickAndPlaceDense-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: TD3
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: FetchPickAndPlaceDense-v2
+      type: FetchPickAndPlaceDense-v2
+    metrics:
+    - type: mean_reward
+      value: -10.95 +/- 6.23
+      name: mean_reward
+      verified: false
+---
+
+# **TD3** Agent playing **FetchPickAndPlaceDense-v2**
+This is a trained model of a **TD3** agent playing **FetchPickAndPlaceDense-v2**
+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
+
+...
+```

config.json

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Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\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 0x7e4a39f4c8b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e4a3a13b280>"}, "verbose": 0, "policy_kwargs": {}, "num_timesteps": 30000, "_total_timesteps": 30000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718748823234506629, "learning_rate": 0.001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": 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+        "bounded_below": "[ True  True  True  True]",
+        "bounded_above": "[ True  True  True  True]",
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+        "low": "[-1. -1. -1. -1.]",
+        "high": "[1. 1. 1. 1.]",
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+        "high_repr": "1.0",
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+    "tau": 0.005,
+    "gamma": 0.99,
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+        "__module__": "stable_baselines3.common.buffers",
+        "__doc__": "\n    Dict Replay buffer used in off-policy algorithms like SAC/TD3.\n    Extends the ReplayBuffer to use dictionary observations\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        Disabled for now (see https://github.com/DLR-RM/stable-baselines3/pull/243#discussion_r531535702)\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
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+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7e4a3a139640>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
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+    "policy_delay": 2,
+    "target_noise_clip": 0.5,
+    "target_policy_noise": 0.2,
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+    },
+    "actor_batch_norm_stats": [],
+    "critic_batch_norm_stats": [],
+    "actor_batch_norm_stats_target": [],
+    "critic_batch_norm_stats_target": []
+}

td3-FetchPickAndPlaceDense-v2/policy.pth

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+- OS: Linux-5.15.133+-x86_64-with-glibc2.31 # 1 SMP Tue Dec 19 13:14:11 UTC 2023
+- Python: 3.10.13
+- Stable-Baselines3: 2.1.0
+- PyTorch: 2.1.2
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 3.0.0
+- Gymnasium: 0.29.0
+- OpenAI Gym: 0.26.2