Hparams-optimized-6

Moonman-Lunar-Lander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:066d6273788a86029e1312cf264a51674c2759cd01a8028be5dcf3366265a421
-size 144800
+oid sha256:1185134b371ce16ce552c3ab053055c3a781f9aaae6e87bf534269cf6fecaa03
+size 146205

Moonman-Lunar-Lander-v2/data

@@ -4,19 +4,19 @@
         ":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 0x7f90fbd67a70>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f90fbd67b00>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f90fbd67b90>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f90fbd67c20>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f90fbd67cb0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f90fbd67d40>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f90fbd67dd0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f90fbd67e60>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f90fbd67ef0>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f90fbd67f80>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f90fbd6d050>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f9a68780320>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9a687803b0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9a68780440>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9a687804d0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f9a68780560>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f9a687805f0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9a68780680>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f9a68780710>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9a687807a0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9a68780830>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9a687808c0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f90fbdbd300>"
+        "_abc_impl": "<_abc_data object at 0x7f9a687ce510>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -41,13 +41,13 @@
         "dtype": "int64",
         "_np_random": null
     },
-    "n_envs": 32,
-    "num_timesteps": 440832,
-    "_total_timesteps": 440000,
+    "n_envs": 64,
+    "num_timesteps": 1048576,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1652327756.410429,
+    "start_time": 1652329003.698861,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,27 +56,27 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="
+        ":serialized:": "gAWVswAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiS0CFlIwBQ5R0lFKULg=="
     },
     "_last_original_obs": null,
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.0018909090909091653,
+    "_current_progress_remaining": -0.04857599999999995,
     "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": 210,
-    "n_steps": 656,
+    "_n_updates": 160,
+    "n_steps": 1024,
     "gamma": 0.997,
     "gae_lambda": 0.98,
     "ent_coef": 0.01,

Moonman-Lunar-Lander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a8f0320989b1a2ead31aaf06658ee323397e4160bc51a7fa489d5606eb60cfc4
+oid sha256:a4df0561411210e389cdd4324f32ba56bebbf3cb8b8511e000065ec1a5991960
 size 84893

Moonman-Lunar-Lander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0067d78b86ce58633ca1779a114459c07b85935f4eb13ad145587d76473dafc7
+oid sha256:baef4022c97b2ce8e3d645fc3cb1fa37e350a049a8c6415e9081cb8eb60255dc
 size 43201

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 256.40 +/- 21.37
+      value: 266.93 +/- 24.72
       name: mean_reward
     task:
       type: reinforcement-learning

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 0x7f90fbd67a70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f90fbd67b00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f90fbd67b90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f90fbd67c20>", "_build": "<function ActorCriticPolicy._build at 0x7f90fbd67cb0>", "forward": "<function ActorCriticPolicy.forward at 0x7f90fbd67d40>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f90fbd67dd0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f90fbd67e60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f90fbd67ef0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f90fbd67f80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f90fbd6d050>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f90fbdbd300>"}, "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": 32, "num_timesteps": 440832, "_total_timesteps": 440000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652327756.410429, "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": -0.0018909090909091653, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 210, "n_steps": 656, "gamma": 0.997, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 32, "n_epochs": 10, "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 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 0x7f9a68780320>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9a687803b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9a68780440>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9a687804d0>", "_build": "<function ActorCriticPolicy._build at 0x7f9a68780560>", "forward": "<function ActorCriticPolicy.forward at 0x7f9a687805f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9a68780680>", "_predict": "<function ActorCriticPolicy._predict at 0x7f9a68780710>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9a687807a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9a68780830>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9a687808c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f9a687ce510>"}, "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": 64, "num_timesteps": 1048576, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652329003.698861, "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:": "gAWVswAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiS0CFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.04857599999999995, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 160, "n_steps": 1024, "gamma": 0.997, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 32, "n_epochs": 10, "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"}}

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c8d3eb171f6af8017b4cabe235f200560c7959dcfe9362c6589abf5b0d19395a
-size 163896
+oid sha256:ad3fa6e7a4c14585a5e68b63d64b81fc90082c7ed9ba0a4f6c8215d4bbb8c5b0
+size 205821

results.json

@@ -1 +1 @@
-{"mean_reward": 256.3958896734528, "std_reward": 21.370762435078465, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-12T04:11:31.266729"}
+{"mean_reward": 266.93487947365674, "std_reward": 24.72430315098258, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-12T04:53:11.854653"}