trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 260.82 +/- 15.02
+      value: 286.98 +/- 22.32
       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 0x7c07027bdbd0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c07027bdc60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c07027bdcf0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c07027bdd80>", "_build": "<function ActorCriticPolicy._build at 0x7c07027bde10>", "forward": "<function ActorCriticPolicy.forward at 0x7c07027bdea0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c07027bdf30>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c07027bdfc0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c07027be050>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c07027be0e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c07027be170>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c07027be200>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c07027c1200>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1697456596101801111, "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": -0.015808000000000044, "_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:": "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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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 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 0x7c07027bdbd0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c07027bdc60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c07027bdcf0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c07027bdd80>", "_build": "<function ActorCriticPolicy._build at 0x7c07027bde10>", "forward": "<function ActorCriticPolicy.forward at 0x7c07027bdea0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c07027bdf30>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c07027bdfc0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c07027be050>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c07027be0e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c07027be170>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c07027be200>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c07027c1200>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2015232, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1697460546306001156, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAABAAAAAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.007616000000000067, "_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": 988, "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:": "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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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 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 sha256:217084f290bac3bb6f417dbbc739c5c152025a6325466fbb3ccc9dd0b5da10f8
-size 146747
+oid sha256:bc71b2679088b1fb52ae3df570218780090bf78454e43e80240bef9c843eb615
+size 146627

ppo-LunarLander-v2/data

@@ -21,37 +21,37 @@
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 2015232,
+    "_total_timesteps": 2000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1697456596101801111,
+    "start_time": 1697460546306001156,
     "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAABAAAAAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
     },
     "_last_original_obs": null,
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.015808000000000044,
+    "_current_progress_remaining": -0.007616000000000067,
     "_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": 248,
+    "_n_updates": 988,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:047c68ed5883a61d440c59c5f337940e56e22e2146cefb5409e0f2932961b187
+oid sha256:f8a98ab0bb6aa62e7746121417fb6db9e8641abb77e66541418049cde2eff84d
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a06eed38efeeeff75b1a5c9516134f7c5ac5588c01423141a1f00fd54a9a99d0
+oid sha256:1960198a7ebd41dd40e98968b65d2f839c22dedb7ebc597392ebd49b4a30616f
 size 43329

results.json

@@ -1 +1 @@
-{"mean_reward": 260.82040960000006, "std_reward": 15.017246744287633, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-16T12:27:44.399266"}
+{"mean_reward": 286.9831422, "std_reward": 22.31595248283012, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-16T13:16:14.553795"}