Lunar Agent Training 1

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 257.62 +/- 20.44
+      value: 282.65 +/- 16.16
       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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671305952814226905, "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": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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, "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 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:": "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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 sha256:53d72ed230ecd9c8624f665c5efe4947c7f92ccb583e2daa92e30a9e07c82fe9
-size 147206
+oid sha256:20c03643ace7e5b5f91fbafb82509f79f3c5509a5926938d449bd5528937d005
+size 147125

ppo-LunarLander-v2/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 1507328,
+    "_total_timesteps": 1500000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1671305952814226905,
+    "start_time": 1671309992360527396,
     "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'>",
@@ -66,24 +66,24 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.015808000000000044,
+    "_current_progress_remaining": -0.004885333333333408,
     "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_steps": 1024,
-    "gamma": 0.999,
-    "gae_lambda": 0.98,
-    "ent_coef": 0.01,
+    "_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": 4,
+    "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:baca273fdf27271caa7f9c9042f46833dd7b7180bb0eb2d5c672e583c4f046b1
+oid sha256:446565d5298f19711bab833008a61101aa86901c95a118a2fced59f52b731482
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:55ab79fd7c51738ce6a52adca89e6e4eb997f95d2d2f93ba06b56e82409f4746
+oid sha256:86af72c3fac965961b2070794239440cd338fc3f4782bfb9466baebc62dc7161
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": 257.6200125348609, "std_reward": 20.441589744291147, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-17T20:06:34.406725"}
+{"mean_reward": 282.6506229947202, "std_reward": 16.16499241447831, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-17T21:15:39.840192"}