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: 281.90 +/- 16.76
+      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 0x7f43cd6991f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f43cd699280>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f43cd699310>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f43cd6993a0>", "_build": "<function ActorCriticPolicy._build at 0x7f43cd699430>", "forward": "<function ActorCriticPolicy.forward at 0x7f43cd6994c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f43cd699550>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f43cd6995e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f43cd699670>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f43cd699700>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f43cd699790>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f43cd699820>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f43cd68bc30>"}, "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": 1676232481063949256, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAEAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 620, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.01, "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 sha256:88f80addb45850eaa7ea1c4c2b7857fd85e3c94c75b17b201be43e8d43650253
+size 147292

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 0x7f43cd6991f0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f43cd699280>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f43cd699310>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f43cd6993a0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f43cd699430>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f43cd6994c0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f43cd699550>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f43cd6995e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f43cd699670>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f43cd699700>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f43cd699790>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f43cd699820>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f43cd68bc30>"
+    },
+    "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": 1676232481063949256,
+    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAEAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 620,
+    "n_steps": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.01,
+    "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 sha256:39ae4eb2d9857f743c9d305cb0bf512f478270918aa5c05e5cc81feba20419cc
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:636dd9da1f89bd8201aa98ad553b41f9fbbea8d51f3fffda83b56c4811961b90
+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": 281.9000595477362, "std_reward": 16.756033045402546, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-12T21:00:29.119131"}