lunar lander v2 PPO 12x100K steps

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 270.56 +/- 22.38
+      value: 283.01 +/- 14.03
       name: mean_reward
     task:
       type: reinforcement-learning

bguan_ppo_lunarlander_220924A.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:52938962dbe6db3bfcc3888b19688097fdd7118d3dc9c2db16e32c3070cb6573
-size 147054
+oid sha256:79d5500ace5a3f930b70ef5433fdc433b82ef847c28d156f036e64c907846489
+size 147051

bguan_ppo_lunarlander_220924A/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 114688,
-    "_total_timesteps": 100000,
+    "num_timesteps": 212992,
+    "_total_timesteps": 200000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1664059285147970939,
+    "start_time": 1664061939092622725,
     "learning_rate": 0.0005,
     "tensorboard_log": "logs",
     "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'>",
@@ -66,19 +66,19 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.1468799999999999,
+    "_current_progress_remaining": -0.0649599999999999,
     "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": 364,
+    "_n_updates": 300,
     "n_steps": 1024,
-    "gamma": 0.999,
-    "gae_lambda": 0.98,
+    "gamma": 0.995,
+    "gae_lambda": 0.985,
     "ent_coef": 0.01,
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,

bguan_ppo_lunarlander_220924A/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:80e09027c6eadb63c0ab12297fac0937bf67c2a922b3dab0d906d21613bbad6b
+oid sha256:e2056646360715584bea304fbdfef3474bc286552c5846ce1bbba3914cb2f4c8
 size 87865

bguan_ppo_lunarlander_220924A/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:94f94dfd034c6441a4c7abe2c19a06bd1a8c2657e060b8cb7771fb6de3222bf5
+oid sha256:e78a983b7f56f7cc36ec5a84ccae34ff254076803dc683a83bdba37e721a1eba
 size 43201

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 0x7f5c11875f80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5c1187c050>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5c1187c0e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5c1187c170>", "_build": "<function ActorCriticPolicy._build at 0x7f5c1187c200>", "forward": "<function ActorCriticPolicy.forward at 0x7f5c1187c290>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5c1187c320>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5c1187c3b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5c1187c440>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5c1187c4d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5c1187c560>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f5c118b9e40>"}, "verbose": 1, "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": 16, "num_timesteps": 114688, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1664059285147970939, "learning_rate": 0.0005, "tensorboard_log": "logs", "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": -0.1468799999999999, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 364, "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-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.14", "Stable-Baselines3": "1.6.1a4", "PyTorch": "1.12.1+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 0x7f5c11875f80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5c1187c050>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5c1187c0e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5c1187c170>", "_build": "<function ActorCriticPolicy._build at 0x7f5c1187c200>", "forward": "<function ActorCriticPolicy.forward at 0x7f5c1187c290>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5c1187c320>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5c1187c3b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5c1187c440>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5c1187c4d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5c1187c560>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f5c118b9e40>"}, "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": 212992, "_total_timesteps": 200000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1664061939092622725, "learning_rate": 0.0005, "tensorboard_log": "logs", "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoH32UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP0BiTdLxqfyFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAI1RVD7tSiU+pXdqvrW6Zb6XCf09spiLvQAAAAAAAAAAgKWNvey8iD5BOzM+3s+KvgnqYzsWtGM8AAAAAAAAAAAAPFU9KThjujpsRb10Tb229bxGu4pqLTYAAAAAAAAAAADNEL0i55I/TBi2vcY4Gb+McaO9gxiJvQAAAAAAAAAA00s4Ps6ilz2vR5u+5dcNvrtshbxOwAE9AAAAAAAAAAAAjr+994BPP/HroLzQwue+XKjqvbXIez0AAAAAAAAAADNbwbxyVLc/wOTqvhzQCz5w1Tg8ncKRvAAAAAAAAAAAGlYnPR/v+7tPHDk4deWFPMr+UL2uWmE9AACAPwAAgD+AwPo9fdxaP6OyXT7fLBO/+73APUnZm70AAAAAAAAAAJqrWDz2zFS6uc8rNG3wq69iA5E7NeCxswAAgD8AAIA/LeC1PofegT7JmcW+6r1iviSsrj2rDtC9AAAAAAAAAACGRrI+Nsv1PsLRgL0aZM6+reZ9PjoP5L0AAAAAAAAAAE3tG76/xnE/5SaJvnHZFL+or2y+8H1ivQAAAAAAAAAATUFevTYAiz79sFs+tPaSvpFemD170pQ9AAAAAAAAAABm8aW8I864P6pZO74h0uE80tmbO/bnkb0AAAAAAAAAADNBlzwfNbO5/w41tIqDRa8uHIQ7dQmiMwAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": -0.0649599999999999, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 300, "n_steps": 1024, "gamma": 0.995, "gae_lambda": 0.985, "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-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.14", "Stable-Baselines3": "1.6.1a4", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": 270.5601603582439, "std_reward": 22.37697072075421, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-09-24T22:49:55.888206"}
+{"mean_reward": 283.0117335891351, "std_reward": 14.029925481022541, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-09-24T23:32:03.446938"}