Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 241.91 +/- 20.30
+      value: 272.00 +/- 17.03
       name: mean_reward
       verified: false
 ---

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 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 0x7e30498b9c60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e30498b9cf0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e30498b9d80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e30498b9e10>", "_build": "<function ActorCriticPolicy._build at 0x7e30498b9ea0>", "forward": "<function ActorCriticPolicy.forward at 0x7e30498b9f30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e30498b9fc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e30498ba050>", "_predict": "<function ActorCriticPolicy._predict at 0x7e30498ba0e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e30498ba170>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e30498ba200>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e30498ba290>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e30498a5200>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1693290663103670362, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAA28uz3hZKe6X+opNIJrRjCtySs4ZsyiswAAgD8AAIA/AFCjOicctD/1OAE+xG8tvq9avLqtKuq8AAAAAAAAAAAa88Q9ezqNus2N7TqE48I1NIm7OuKrCboAAIA/AAAAALNDlz09dwq7UGrmu5QusjxX8/M7066YvQAAgD8AAIA/5V2MvrzLdT8dWIu6laKqvkS/BL7eVLo8AAAAAAAAAAD6VVw+bAWEP0ljpT2KFlO+bbsUPmL1Q7wAAAAAAAAAAIYgSj7S7hs/AKzjvZMoQ77SGto8a5YKvAAAAAAAAAAArXVOPi4b2bwD5N47N21+urNrQb7kqTu7AACAPwAAgD8z/ZC8SMuguv1+LTmJMCM00RoQOawlR7gAAIA/AACAP51iXr6CKxs+kPhUPuWZUr6Qw9i8rRY3PQAAAAAAAAAANpNyvgduHz5KJiQ+d0aPvhPMlLmHwbU9AAAAAAAAAACITra+Cw1MP1sa3j0Dx32+9xHfvfvQmj0AAAAAAAAAAM05Ab1Dwqo/HXbavh3t/b6o0wA9bp1QPQAAAAAAAAAAzXPsPT3HPruiwCG+FcYWPKp9Pz3w4E++AACAPwAAgD96OKC+FStfP/LLo71nZH++Q75Rvg65yj0AAAAAAAAAAKaMrz2Ptju6RWR+O1VkwTi/r0U74hcTugAAgD8AAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAABAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
+{"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 0x7fb3b7b568c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb3b7b56950>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb3b7b569e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb3b7b56a70>", "_build": "<function ActorCriticPolicy._build at 0x7fb3b7b56b00>", "forward": "<function ActorCriticPolicy.forward at 0x7fb3b7b56b90>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fb3b7b56c20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb3b7b56cb0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fb3b7b56d40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb3b7b56dd0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb3b7b56e60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb3b7b56ef0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fb3b7b4b5c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1693298652263792172, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 32, "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": 32, "n_epochs": 8, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:92576716f46b76f22a511db598c42e08d31fff61379193f2597afeac1d37023e
-size 146750
+oid sha256:99b6b144fd081074d351890170c6a8aa434078390899e5cca9ff278aa3639ca2
+size 147442

ppo-LunarLander-v2/data

@@ -4,20 +4,20 @@
         ":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 0x7e30498b9c60>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e30498b9cf0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e30498b9d80>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e30498b9e10>",
-        "_build": "<function ActorCriticPolicy._build at 0x7e30498b9ea0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7e30498b9f30>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e30498b9fc0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e30498ba050>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7e30498ba0e0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e30498ba170>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e30498ba200>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e30498ba290>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7fb3b7b568c0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb3b7b56950>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb3b7b569e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb3b7b56a70>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fb3b7b56b00>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fb3b7b56b90>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fb3b7b56c20>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb3b7b56cb0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fb3b7b56d40>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb3b7b56dd0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb3b7b56e60>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb3b7b56ef0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7e30498a5200>"
+        "_abc_impl": "<_abc._abc_data object at 0x7fb3b7b4b5c0>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -26,16 +26,16 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1693290663103670362,
+    "start_time": 1693298652263792172,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAABAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="
     },
     "_last_original_obs": null,
     "_episode_num": 0,
@@ -45,7 +45,7 @@
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
@@ -76,15 +76,15 @@
         "dtype": "int64",
         "_np_random": null
     },
-    "n_envs": 16,
+    "n_envs": 32,
     "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,
+    "batch_size": 32,
+    "n_epochs": 8,
     "clip_range": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c618a91fd6669dbd3d78b9442dd6f317005c5d0289d266fd3ea8d4847dbc5d21
+oid sha256:cd5dfacc57adae0e75d37d00affbf0fa7860f34e57d7276ad784e0a92b5cc67d
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0837a94fab4af582b37c21dbc1636e62e9d9398111f5f94cde895df801ec0a33
+oid sha256:008d7d0dcfd71574ec4eb5de4e18d2165cb50d3b9e273dd66f6ca6812a2f3d14
 size 43329

results.json

@@ -1 +1 @@
-{"mean_reward": 241.907037163029, "std_reward": 20.29517114255565, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-08-29T06:55:20.078763"}
+{"mean_reward": 271.9971113420637, "std_reward": 17.027414777406207, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-08-29T09:18:52.681077"}