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: 277.85 +/- 21.43
+      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 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 0x7fb7ea510ca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb7ea510d30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb7ea510dc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb7ea510e50>", "_build": "<function ActorCriticPolicy._build at 0x7fb7ea510ee0>", "forward": "<function ActorCriticPolicy.forward at 0x7fb7ea510f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb7ea497040>", "_predict": "<function ActorCriticPolicy._predict at 0x7fb7ea4970d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb7ea497160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb7ea4971f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb7ea497280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fb7ea50f420>"}, "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": 1671455085146822617, "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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+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:ec35b02b6e23d9867a5489ce82d912f6c603b2971fa45e6419e1d951bdec553a
+size 147142

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.2

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 0x7fb7ea510ca0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb7ea510d30>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb7ea510dc0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb7ea510e50>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fb7ea510ee0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fb7ea510f70>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb7ea497040>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fb7ea4970d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb7ea497160>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb7ea4971f0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb7ea497280>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fb7ea50f420>"
+    },
+    "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": 1671455085146822617,
+    "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:e523aca2c8df2bed27f409a7ebdf7cbae68d3d253f5a78c9672844150a7c63e3
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b5fcd2eb047650e0e9fbc2914aaf75d66ccb0bb76fd6829217f12288f7dd7de1
+size 43201

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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.8.16
+Stable-Baselines3: 1.6.2
+PyTorch: 1.13.0+cu116
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 277.85098124978924, "std_reward": 21.434590751107617, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-19T13:20:57.057976"}