Upload PPO LunarLander-v2 trained agent

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: -216.83 +/- 153.68
+      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 0x7f3394ac1820>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3394ac18b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3394ac1940>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3394ac19d0>", "_build": "<function ActorCriticPolicy._build at 0x7f3394ac1a60>", "forward": "<function ActorCriticPolicy.forward at 0x7f3394ac1af0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f3394ac1b80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3394ac1c10>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3394ac1ca0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3394ac1d30>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3394ac1dc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3394ac1e50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f3394ac33c0>"}, "verbose": 1, "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": 16384, "_total_timesteps": 10000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1680470654002193181, "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": -0.6384000000000001, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 4, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1163bed8e0a590f2a4120c9b541ef9220a97e9e3b853b67cc6aef67b733592ec
+size 147289

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 0x7f3394ac1820>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3394ac18b0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3394ac1940>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3394ac19d0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f3394ac1a60>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f3394ac1af0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f3394ac1b80>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3394ac1c10>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f3394ac1ca0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3394ac1d30>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3394ac1dc0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3394ac1e50>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f3394ac33c0>"
+    },
+    "verbose": 1,
+    "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": 16384,
+    "_total_timesteps": 10000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1680470654002193181,
+    "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": -0.6384000000000001,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 4,
+    "n_steps": 1024,
+    "gamma": 0.999,
+    "gae_lambda": 0.98,
+    "ent_coef": 0.01,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 4,
+    "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 sha256:7cdb55373dfcc7a16dd1b2955934e87774d993281aafff0bc7a56a66924f143c
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1e04de0f954ac9974cce87dcd0354bdb127ef05f831e7d2e8eec63430ad3cc9a
+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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
+- Python: 3.9.16
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu116
+- GPU Enabled: True
+- Numpy: 1.22.4
+- Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": -216.83045750956518, "std_reward": 153.67738485762027, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-02T21:25:25.613354"}