New LunarLander

README.md

@@ -6,23 +6,32 @@ tags:
 - reinforcement-learning
 - stable-baselines3
 model-index:
-- name: ppo-MlpPolicy
+- name: PPO
   results:
-  - metrics:
-    - type: mean_reward
-      value: 233.66 +/- 36.77
-      name: mean_reward
-    task:
+  - task:
       type: reinforcement-learning
       name: reinforcement-learning
     dataset:
       name: LunarLander-v2
       type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 257.30 +/- 18.04
+      name: mean_reward
+      verified: false
 ---
 
-  # **ppo-MlpPolicy** Agent playing **LunarLander-v2**
-  This is a trained model of a **ppo-MlpPolicy** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
-  
-  ## Usage (with Stable-baselines3)
-  TODO: Add your code
-  
+# **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

@@ -1 +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 0x7f0166a89680>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0166a89710>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0166a897a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0166a89830>", "_build": "<function ActorCriticPolicy._build at 0x7f0166a898c0>", "forward": "<function ActorCriticPolicy.forward at 0x7f0166a89950>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0166a899e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0166a89a70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0166a89b00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0166a89b90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0166a89c20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0166ae3150>"}, "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": 1651864704.7172234, "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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
+{"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 0x7efc295cbb80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efc295cbc10>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efc295cbca0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efc295cbd30>", "_build": "<function ActorCriticPolicy._build at 0x7efc295cbdc0>", "forward": "<function ActorCriticPolicy.forward at 0x7efc295cbe50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7efc295cbee0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efc295cbf70>", "_predict": "<function ActorCriticPolicy._predict at 0x7efc295cf040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efc295cf0d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efc295cf160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efc295cf1f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7efc295d0100>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1680600779791270847, "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": 372, "n_steps": 1024, "gamma": 0.9995, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 6, "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": "2.0.0+cu118", "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 sha256:37538ad24d789a0c3ef70329b615162c1445973b5b08386b017dff4dae40cb00
+size 147429

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 0x7efc295cbb80>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efc295cbc10>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efc295cbca0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efc295cbd30>",
+        "_build": "<function ActorCriticPolicy._build at 0x7efc295cbdc0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7efc295cbe50>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7efc295cbee0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efc295cbf70>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7efc295cf040>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efc295cf0d0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efc295cf160>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efc295cf1f0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7efc295d0100>"
+    },
+    "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": 1680600779791270847,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
+    },
+    "_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": 372,
+    "n_steps": 1024,
+    "gamma": 0.9995,
+    "gae_lambda": 0.98,
+    "ent_coef": 0.01,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 6,
+    "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 sha256:6955279dc4cee91770c04293a74b1db6696d93ab3f23a1bccbfcb857bb01e269
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:789f78f01f3a4b711ed8bb1d52a9fb95eb37851ed29273d05f166f39ff178298
+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: 2.0.0+cu118
+- GPU Enabled: True
+- Numpy: 1.22.4
+- Gym: 0.21.0

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:690189da627224c8ff897e3c9b3934c2a1175f19faa7d4bee85a40b90b16b57c
-size 251814
+oid sha256:1711529a2e85da3456aa4c72993f41cff89cfdc583524fff0ed255a67dbc0515
+size 231375

results.json

@@ -1 +1 @@
-{"mean_reward": 233.65577190637342, "std_reward": 36.76798565399029, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-06T19:33:39.333100"}
+{"mean_reward": 257.29682963677124, "std_reward": 18.044423918134076, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-04T09:59:09.132456"}