3rd commit

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 223.82 +/- 51.99
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **LunarLander-v2**
+This is a trained model of a **PPO** agent playing **LunarLander-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

@@ -0,0 +1 @@
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\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 ortho_init: Whether to use or not orthogonal initialization\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 full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\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 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 0x7f7400ea51f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7400ea5280>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7400ea5310>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7400ea53a0>", "_build": "<function ActorCriticPolicy._build at 0x7f7400ea5430>", "forward": "<function ActorCriticPolicy.forward at 0x7f7400ea54c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7400ea5550>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7400ea55e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7400ea5670>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7400ea5700>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7400ea5790>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7400ea5820>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7400e9e900>"}, "verbose": 0, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1675148246484185169, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 310, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ab99c282e846f7894e9bab51f97d45e0060877a9b42116ce96b6597aea006626
+size 147407

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.7.0

ppo-LunarLander-v2/data

@@ -0,0 +1,95 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
+        "__module__": "stable_baselines3.common.policies",
+        "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\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 ortho_init: Whether to use or not orthogonal initialization\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 full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\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 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 0x7f7400ea51f0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7400ea5280>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7400ea5310>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7400ea53a0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f7400ea5430>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f7400ea54c0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7400ea5550>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7400ea55e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f7400ea5670>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7400ea5700>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7400ea5790>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7400ea5820>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f7400e9e900>"
+    },
+    "verbose": 0,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            8
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False]",
+        "bounded_above": "[False False False False False False False False]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        "n": 4,
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1675148246484185169,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.015808000000000044,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 310,
+    "n_steps": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 10,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9409edb260388fd181cae7b8254046c332540793da755b88a81242ab9d3c8a9a
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:88f3955eb4eb3d7012efcc59388bc36c547b0773634bd427a155f129ffc38ea8
+size 43393

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,7 @@
+- OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
+- Python: 3.8.10
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu116
+- GPU Enabled: True
+- Numpy: 1.21.6
+- Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 223.81789077174454, "std_reward": 51.98972118164829, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-31T07:24:38.696682"}