Lunar Agent Training 1

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 282.65 +/- 16.16
+      value: 291.16 +/- 14.26
       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 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 0x7f0bcae5eca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0bcae5ed30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0bcae5edc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0bcae5ee50>", "_build": "<function ActorCriticPolicy._build at 0x7f0bcae5eee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f0bcae5ef70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0bcae62040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0bcae620d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0bcae62160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0bcae621f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0bcae62280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0bcae5b450>"}, "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": 16, "num_timesteps": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671309992360527396, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.004885333333333408, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 616, "n_steps": 2048, "gamma": 0.9995, "gae_lambda": 0.985, "ent_coef": 0.015, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 8, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "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 0x7f8007878280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8007878310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f80078783a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8007878430>", "_build": "<function ActorCriticPolicy._build at 0x7f80078784c0>", "forward": "<function ActorCriticPolicy.forward at 0x7f8007878550>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f80078785e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8007878670>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8007878700>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8007878790>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8007878820>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f800786fe70>"}, "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": 16, "num_timesteps": 5013504, "_total_timesteps": 5000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671392219240494541, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0027007999999999477, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1224, "n_steps": 2048, "gamma": 0.9995, "gae_lambda": 0.985, "ent_coef": 0.015, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 8, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:20c03643ace7e5b5f91fbafb82509f79f3c5509a5926938d449bd5528937d005
-size 147125
+oid sha256:9b7727b8701882250a54ffff6917b44ab82524d0c16f95468c0ee2d62b93ce7f
+size 147091

ppo-LunarLander-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 0x7f0bcae5eca0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0bcae5ed30>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0bcae5edc0>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0bcae5ee50>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f0bcae5eee0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f0bcae5ef70>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0bcae62040>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f0bcae620d0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0bcae62160>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0bcae621f0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0bcae62280>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f8007878280>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8007878310>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f80078783a0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8007878430>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f80078784c0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f8007878550>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f80078785e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f8007878670>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8007878700>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8007878790>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8007878820>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f0bcae5b450>"
+        "_abc_impl": "<_abc_data object at 0x7f800786fe70>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 1507328,
-    "_total_timesteps": 1500000,
+    "num_timesteps": 5013504,
+    "_total_timesteps": 5000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1671309992360527396,
+    "start_time": 1671392219240494541,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,16 +66,16 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.004885333333333408,
+    "_current_progress_remaining": -0.0027007999999999477,
     "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": 616,
+    "_n_updates": 1224,
     "n_steps": 2048,
     "gamma": 0.9995,
     "gae_lambda": 0.985,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:446565d5298f19711bab833008a61101aa86901c95a118a2fced59f52b731482
+oid sha256:a83de97a6f197c0df9c249662917cff507baeafb395f2e29b368fa12033d0e28
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:86af72c3fac965961b2070794239440cd338fc3f4782bfb9466baebc62dc7161
+oid sha256:a472758e24304384e57cab15ca899970f80b72ee8c448c9a6c64a0b02f5a7f1f
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": 282.6506229947202, "std_reward": 16.16499241447831, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-17T21:15:39.840192"}
+{"mean_reward": 291.155389849093, "std_reward": 14.260690702566421, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-18T21:05:15.394367"}