Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 290.09 +/- 17.84
+      value: 292.16 +/- 19.84
       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 0x00000176295A1360>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x00000176295A13F0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x00000176295A1480>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x00000176295A1510>", "_build": "<function ActorCriticPolicy._build at 0x00000176295A15A0>", "forward": "<function ActorCriticPolicy.forward at 0x00000176295A1630>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x00000176295A16C0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x00000176295A1750>", "_predict": "<function ActorCriticPolicy._predict at 0x00000176295A17E0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x00000176295A1870>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x00000176295A1900>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x00000176295A1990>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x000001762959B2C0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 5013504, "_total_timesteps": 5000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711148583651035700, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0027007999999999477, "_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": 9180, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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": 30, "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": "Windows-10-10.0.22000-SP0 10.0.22000", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cpu", "GPU Enabled": "False", "Numpy": "1.26.4", "Cloudpickle": "3.0.0", "Gymnasium": "0.28.1"}}
+{"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 0x7b9511f231c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b9511f23250>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b9511f232e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b9511f23370>", "_build": "<function ActorCriticPolicy._build at 0x7b9511f23400>", "forward": "<function ActorCriticPolicy.forward at 0x7b9511f23490>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b9511f23520>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b9511f235b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7b9511f23640>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b9511f236d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b9511f23760>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b9511f237f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b95120cad80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 3014656, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711225428487455303, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.004885333333333408, "_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": 7360, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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": 40, "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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "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:cdb0444bcb20cd470c2a00d19bd7e3e3b12fbca08bd884050f5f1731a4a2a2d0
-size 147173
+oid sha256:62b8f00a59ff9d6acf1a296489ea734fced194a49b017a79c5ee6221857977ea
+size 147451

ppo-LunarLander-v2/data

@@ -4,34 +4,34 @@
         ":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 0x00000176295A1360>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x00000176295A13F0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x00000176295A1480>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x00000176295A1510>",
-        "_build": "<function ActorCriticPolicy._build at 0x00000176295A15A0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x00000176295A1630>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x00000176295A16C0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x00000176295A1750>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x00000176295A17E0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x00000176295A1870>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x00000176295A1900>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x00000176295A1990>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7b9511f231c0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b9511f23250>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b9511f232e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b9511f23370>",
+        "_build": "<function ActorCriticPolicy._build at 0x7b9511f23400>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7b9511f23490>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b9511f23520>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b9511f235b0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7b9511f23640>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b9511f236d0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b9511f23760>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b9511f237f0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x000001762959B2C0>"
+        "_abc_impl": "<_abc._abc_data object at 0x7b95120cad80>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 5013504,
-    "_total_timesteps": 5000000,
+    "num_timesteps": 3014656,
+    "_total_timesteps": 3000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1711148583651035700,
+    "start_time": 1711225428487455303,
     "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'>",
@@ -41,17 +41,17 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.0027007999999999477,
+    "_current_progress_remaining": -0.004885333333333408,
     "_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'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 9180,
+    "_n_updates": 7360,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",
@@ -84,16 +84,16 @@
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,
     "batch_size": 64,
-    "n_epochs": 30,
+    "n_epochs": 40,
     "clip_range": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":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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"
+        ":serialized:": "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"
     }
 }

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3a4a4a7dedd3f4e99cb5197876d8cf73ecfd827a3bf6555679549843b7b172c1
+oid sha256:a6309e89709d45b68ae81905ec8845a0c9c3f7003ca6b67ac5baa4581f17b569
 size 87978

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bb3b4dd67c04b338a6cfec903400c40523c011841bf75ac82b99512fe778d631
+oid sha256:83c07aad9194c0828c96fd50f44aa034e3d948182e4f54ab595194becca8fdfa
 size 43634

ppo-LunarLander-v2/pytorch_variables.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fb4dde0c1ad63b7740276006a06cc491b21b407ea6c889928c223ec77ddad79f
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
 size 864

ppo-LunarLander-v2/system_info.txt

@@ -1,8 +1,9 @@
-- OS: Windows-10-10.0.22000-SP0 10.0.22000
-- Python: 3.10.11
+- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
+- Python: 3.10.12
 - Stable-Baselines3: 2.0.0a5
-- PyTorch: 2.2.1+cpu
+- PyTorch: 2.2.1+cu121
 - GPU Enabled: False
-- Numpy: 1.26.4
-- Cloudpickle: 3.0.0
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
 - Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -1 +1 @@
-{"mean_reward": 290.08621500825416, "std_reward": 17.842668577766993, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-23T11:29:44.116168"}
+{"mean_reward": 292.16051978167815, "std_reward": 19.838880452940646, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-23T23:41:34.703561"}