First PPO model

README.md

@@ -8,16 +8,17 @@ tags:
 model-index:
 - name: PPO
   results:
-  - metrics:
-    - type: mean_reward
-      value: 192.58 +/- 81.25
-      name: mean_reward
-    task:
+  - task:
       type: reinforcement-learning
       name: reinforcement-learning
     dataset:
       name: LunarLander-v2
       type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 237.15 +/- 93.32
+      name: mean_reward
+      verified: false
 ---
 
 # **PPO** Agent playing **LunarLander-v2**

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 0x7fd24401f0a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd24401f130>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd24401f1c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd24401f250>", "_build": "<function ActorCriticPolicy._build at 0x7fd24401f2e0>", "forward": "<function ActorCriticPolicy.forward at 0x7fd24401f370>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd24401f400>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd24401f490>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd24401f520>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd24401f5b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd24401f640>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd244136580>"}, "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:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1657290493.8497398, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": null, "_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-5.13.0-52-generic-x86_64-with-glibc2.31 #59~20.04.1-Ubuntu SMP Thu Jun 16 21:21:28 UTC 2022", "Python": "3.10.4", "Stable-Baselines3": "1.5.0", "PyTorch": "1.12.0", "GPU Enabled": "True", "Numpy": "1.22.3", "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 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 0x7f5167f47910>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5167f479a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5167f47a30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5167f47ac0>", "_build": "<function ActorCriticPolicy._build at 0x7f5167f47b50>", "forward": "<function ActorCriticPolicy.forward at 0x7f5167f47be0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5167f47c70>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5167f47d00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5167f47d90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5167f47e20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5167f47eb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f5167f50800>"}, "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": 32, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671130458394823896, "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="}, "_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": 512, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWVCQMAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjGwvaG9tZS9zZWJhc3RpYW4vYW5hY29uZGEzL2VudnMvaHVnZ2luZ0ZhY2VfUkwvbGliL3B5dGhvbjMuMTAvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjGwvaG9tZS9zZWJhc3RpYW4vYW5hY29uZGEzL2VudnMvaHVnZ2luZ0ZhY2VfUkwvbGliL3B5dGhvbjMuMTAvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoIH2UfZQoaBdoDowMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBiMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.15.0-56-generic-x86_64-with-glibc2.31 #62~20.04.1-Ubuntu SMP Tue Nov 22 21:24:20 UTC 2022", "Python": "3.10.4", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.0", "GPU Enabled": "True", "Numpy": "1.22.3", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:befcebbb14bcf331eab5d3b174341bc61a64f247dedaed49f9f198cb2c8d9d5d
-size 146495
+oid sha256:56664bcd26702bd362b8fc17cfb46a4cca80f1a03bbf89d36573d5b2ecfd15a0
+size 147982

ppo-LunarLander-v2/_stable_baselines3_version

@@ -1 +1 @@
-1.5.0
+1.6.2

ppo-LunarLander-v2/data

@@ -4,25 +4,25 @@
         ":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 0x7fd24401f0a0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd24401f130>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd24401f1c0>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd24401f250>",
-        "_build": "<function ActorCriticPolicy._build at 0x7fd24401f2e0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7fd24401f370>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd24401f400>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7fd24401f490>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd24401f520>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd24401f5b0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd24401f640>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f5167f47910>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5167f479a0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5167f47a30>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5167f47ac0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f5167f47b50>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f5167f47be0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5167f47c70>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f5167f47d00>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5167f47d90>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5167f47e20>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5167f47eb0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7fd244136580>"
+        "_abc_impl": "<_abc._abc_data object at 0x7f5167f50800>"
     },
-    "verbose": 1,
+    "verbose": 0,
     "policy_kwargs": {},
     "observation_space": {
         ":type:": "<class 'gym.spaces.box.Box'>",
-        ":serialized:": "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",
+        ":serialized:": "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",
         "dtype": "float32",
         "_shape": [
             8
@@ -35,29 +35,32 @@
     },
     "action_space": {
         ":type:": "<class 'gym.spaces.discrete.Discrete'>",
-        ":serialized:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
         "n": 4,
         "_shape": [],
         "dtype": "int64",
         "_np_random": null
     },
-    "n_envs": 16,
-    "num_timesteps": 507904,
-    "_total_timesteps": 500000,
+    "n_envs": 32,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1657290493.8497398,
+    "start_time": 1671130458394823896,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"
     },
-    "_last_obs": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="
     },
     "_last_original_obs": null,
     "_episode_num": 0,
@@ -66,24 +69,24 @@
     "_current_progress_remaining": -0.015808000000000044,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 124,
-    "n_steps": 1024,
+    "_n_updates": 620,
+    "n_steps": 512,
     "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,
+    "batch_size": 128,
+    "n_epochs": 10,
     "clip_range": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "clip_range_vf": null,
     "normalize_advantage": true,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7272a7a227438765a5a8ae1e93e3fb6a7dda997d5b5312c4031ee9866151c585
-size 87993
+oid sha256:89617f4e6539d6fdb62219ea4d93bc9ec24db8333f03a6271f58aec83e0b417a
+size 87865

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bcdf4a32e32d9a78d9f7078e2739fa2715bb0403aac7042096f1fff4702a3bee
+oid sha256:4bafcee752d3f85946ae86369e89cf14b0b087c848e6562af136947f0146071f
 size 43201

ppo-LunarLander-v2/system_info.txt

@@ -1,6 +1,6 @@
-OS: Linux-5.13.0-52-generic-x86_64-with-glibc2.31 #59~20.04.1-Ubuntu SMP Thu Jun 16 21:21:28 UTC 2022
+OS: Linux-5.15.0-56-generic-x86_64-with-glibc2.31 #62~20.04.1-Ubuntu SMP Tue Nov 22 21:24:20 UTC 2022
 Python: 3.10.4
-Stable-Baselines3: 1.5.0
+Stable-Baselines3: 1.6.2
 PyTorch: 1.12.0
 GPU Enabled: True
 Numpy: 1.22.3

results.json

@@ -1 +1 @@
-{"mean_reward": 192.57630285017677, "std_reward": 81.2466621933505, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-07-09T17:23:31.702709"}
+{"mean_reward": 237.1476707205166, "std_reward": 93.3205473746058, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-15T16:55:58.705918"}