Initial training run

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 278.91 +/- 18.54
+      value: 285.31 +/- 28.68
       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 0x7f7bd352c5e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7bd352c670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7bd352c700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7bd352c790>", "_build": "<function ActorCriticPolicy._build at 0x7f7bd352c820>", "forward": "<function ActorCriticPolicy.forward at 0x7f7bd352c8b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7bd352c940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7bd352c9d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7bd352ca60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7bd352caf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7bd352cb80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7bd3522e70>"}, "verbose": 0, "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": 8, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670711393395344047, "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:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="}, "_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": 1984, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 32, "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 0x7f2051d1cd30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2051d1cdc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2051d1ce50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2051d1cee0>", "_build": "<function ActorCriticPolicy._build at 0x7f2051d1cf70>", "forward": "<function ActorCriticPolicy.forward at 0x7f2051d22040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2051d220d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2051d22160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2051d221f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2051d22280>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2051d22310>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2051d1d210>"}, "verbose": 0, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 8, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670786404348067830, "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:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="}, "_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": 1984, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.015, "vf_coef": 0.5, "max_grad_norm": 0.35, "batch_size": 128, "n_epochs": 32, "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 sha256:7177e46aae1ffab44eed2c424c39430b60866008be9211810559c5ef9a16d7a2
-size 146732
+oid sha256:2498b156f14019f3ca23d51d4ae01412b0a0a98f26ecc22c8192cd4c6dbf28d0
+size 146866

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 0x7f7bd352c5e0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7bd352c670>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7bd352c700>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7bd352c790>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f7bd352c820>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f7bd352c8b0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7bd352c940>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f7bd352c9d0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7bd352ca60>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7bd352caf0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7bd352cb80>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f2051d1cd30>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2051d1cdc0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2051d1ce50>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2051d1cee0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f2051d1cf70>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f2051d22040>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2051d220d0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f2051d22160>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2051d221f0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2051d22280>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2051d22310>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f7bd3522e70>"
+        "_abc_impl": "<_abc_data object at 0x7f2051d1d210>"
     },
     "verbose": 0,
     "policy_kwargs": {},
@@ -47,7 +47,7 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1670711393395344047,
+    "start_time": 1670786404348067830,
     "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'>",
@@ -69,7 +69,7 @@
     "_current_progress_remaining": -0.015808000000000044,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
@@ -79,9 +79,9 @@
     "n_steps": 2048,
     "gamma": 0.999,
     "gae_lambda": 0.98,
-    "ent_coef": 0.01,
+    "ent_coef": 0.015,
     "vf_coef": 0.5,
-    "max_grad_norm": 0.5,
+    "max_grad_norm": 0.35,
     "batch_size": 128,
     "n_epochs": 32,
     "clip_range": {

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4e832c9455b5283db237a301b868f123d41258f8f6847677cbe812cf4b583cae
+oid sha256:18c8d72a3a76e1a774e5c61b4ae4f108ebb28d68b985f2fab57dec98a9431928
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:64062ba3ae0d13e61fa7391684fbc909c198520c59ec14740c9284228b025734
+oid sha256:762ea50dbaf62d13656852a6acdfde550edee4db1eb4aefd1a3e615e6552b1b9
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": 278.91090946998986, "std_reward": 18.53603208652666, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-10T23:28:44.917252"}
+{"mean_reward": 285.30866639765424, "std_reward": 28.676550945046486, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-11T19:56:32.277240"}