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: 276.44 +/- 18.34
+      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 0x7f6f1a0cbe50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6f1a0cbee0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6f1a0cbf70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6f1a0d1040>", "_build": "<function ActorCriticPolicy._build at 0x7f6f1a0d10d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f6f1a0d1160>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f6f1a0d11f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6f1a0d1280>", "_predict": "<function ActorCriticPolicy._predict at 0x7f6f1a0d1310>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6f1a0d13a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6f1a0d1430>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6f1a0d14c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f6f1a0d0640>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679644719496770483, "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": 248, "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:cf1044ea2fc500e8c6adb4f628b76f74549ce9733eeae5e8ce6cfea14d6eac7f
+size 147417

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 0x7f6f1a0cbe50>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6f1a0cbee0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6f1a0cbf70>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6f1a0d1040>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f6f1a0d10d0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f6f1a0d1160>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f6f1a0d11f0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6f1a0d1280>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f6f1a0d1310>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6f1a0d13a0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6f1a0d1430>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6f1a0d14c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f6f1a0d0640>"
+    },
+    "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": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1679644719496770483,
+    "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": 248,
+    "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 sha256:1059e642922908e62578cc23210241cac38a962100bc286809633b7050f90efa
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:78f1f7fc4be11677e9dcf7c08401125bfa8d4db23a863c03378b1cd058e2a4b8
+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": 276.44476801425435, "std_reward": 18.344079383895558, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-24T08:19:27.992135"}