Upload PPO LunarLander-v2 trained agent

.gitattributes

@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,36 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 206.01 +/- 15.53
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+---
+
+# **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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f59e6a589d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f59e6a58a60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f59e6a58af0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f59e6a58b80>", "_build": "<function ActorCriticPolicy._build at 0x7f59e6a58c10>", "forward": "<function ActorCriticPolicy.forward at 0x7f59e6a58ca0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f59e6a58d30>", "_predict": "<function ActorCriticPolicy._predict at 0x7f59e6a58dc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f59e6a58e50>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f59e6a58ee0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f59e6a58f70>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f59e6a56c80>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1656594784.6548717, "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": 124, "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-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.35 #1 SMP Wed Mar 2 00:30:59 UTC 2022", "Python": "3.9.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.12.0+cu102", "GPU Enabled": "False", "Numpy": "1.22.3", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0014b83d5901c0fe2512778a0326dbaf46b8d938a4ff29127eee60a41c284517
+size 146721

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.5.0

ppo-LunarLander-v2/data

@@ -0,0 +1,94 @@
+{
+    "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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f59e6a589d0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f59e6a58a60>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f59e6a58af0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f59e6a58b80>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f59e6a58c10>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f59e6a58ca0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f59e6a58d30>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f59e6a58dc0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f59e6a58e50>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f59e6a58ee0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f59e6a58f70>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f59e6a56c80>"
+    },
+    "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": 507904,
+    "_total_timesteps": 500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1656594784.6548717,
+    "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": 124,
+    "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 sha256:338970654efca0dc6f50699372d47e2fc4e2a2034bef257072448c232b7d4837
+size 87545

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:32aeaa799924c306fa86934551b4f2f41aff20f5596c6934739d6217247ea012
+size 43073

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-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.35 #1 SMP Wed Mar 2 00:30:59 UTC 2022
+Python: 3.9.13
+Stable-Baselines3: 1.5.0
+PyTorch: 1.12.0+cu102
+GPU Enabled: False
+Numpy: 1.22.3
+Gym: 0.21.0

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:af7167f4aa9a66766c92f2cedf9effe73608837a1a1a15fa8ec7ef333a57d4c6
+size 221357

results.json

@@ -0,0 +1 @@
+{"mean_reward": 206.01439674635034, "std_reward": 15.527294078610803, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-30T21:57:40.608423"}