Upload model: PPO-LunarLander-v2, version: 6.000000

PPO-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2b79078e13d6833497654a510871d7c8a398e37e5391e6806819d870c245d5b7
-size 143984
+oid sha256:fc6611669481ee3c433d3fd97f3c6c8d84d75d692bcc3572d2f94f3c151b8b48
+size 143982

PPO-LunarLander-v2/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 507904,
-    "_total_timesteps": 500000,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1651688624.5959353,
+    "start_time": 1651690616.387879,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAM3pOj00BqA+deMJvXEVyL78qOM7viRROgAAAAAAAAAAhgwDvvzQqT+gZxK/blTjvpF4S76pv5i+AAAAAAAAAABmLby85e2CP4Iku7zpSQa/ncc6vcI32boAAAAAAAAAAHPziD3sM867DZ5ZuwSwwjw33SA95kWivQAAgD8AAIA/wg2Vvs+2MD+iMNQ+d2DIvm9HCb4iNpw+AAAAAAAAAACzPHA9ygFXP6c7gT2+xAG/BajPPX1sRjwAAAAAAAAAAM0kZbvhJIq6rgUts4e5j63Guzi7iFHRMwAAgD8AAIA/s/ISPujQbj9tNV0+M3Psvq/jmj71X/08AAAAAAAAAAAzd9w841KwP2YqfD5lLYm+2/zoPMolDD4AAAAAAAAAAACmm7xZuTc+7Tv3Pv2jmr6uGMk9waCVPgAAAAAAAAAAs+fVvVhL7j7uQ5E9FkLGvgo1tr3zpoY9AAAAAAAAAAAzJ4A87LWjuwH8BT2BQcw88N4Ivc0gqz0AAIA/AACAP5r8H71S1f88NHYDPrPnpb5+I8I9tt4NvQAAAAAAAAAAwLw9vldAFz8Hlq89L7Lovvcxa76enPg9AAAAAAAAAADGRgW+wnghP0Dg8zwkk9y++ABHvu37lD0AAAAAAAAAAKbS/T2F3Yi7zfunvEEhijzfncu8AvxrPQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -69,13 +69,13 @@
     "_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'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 776,
+    "_n_updates": 1272,
     "n_steps": 1024,
     "gamma": 0.999,
     "gae_lambda": 0.98,

PPO-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f6c333596fafcc2331819798a737b3e09c9471b57c37e101ed3f1a861f179b3a
+oid sha256:699d2a648b1c34be0d061e452c3df92cb3e9ae14f8e54f2666bcce14e56d2c1b
 size 84893

PPO-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:62318e2c490d8200fa4f1b6ee2fc6a165cb3bf52357eeda02b8b6dd9f3c9a2a5
+oid sha256:675ad9249f2249db3fc097e285c5acfce045f9858b89112608f8507374439db0
 size 43201

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 284.45 +/- 12.53
+      value: 292.63 +/- 17.52
       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 0x7fcf5c4725f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcf5c472680>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcf5c472710>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcf5c4727a0>", "_build": "<function ActorCriticPolicy._build at 0x7fcf5c472830>", "forward": "<function ActorCriticPolicy.forward at 0x7fcf5c4728c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcf5c472950>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcf5c4729e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcf5c472a70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcf5c472b00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcf5c472b90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcf5c4be720>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651688624.5959353, "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": 776, "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:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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 0x7fcf5c4725f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcf5c472680>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcf5c472710>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcf5c4727a0>", "_build": "<function ActorCriticPolicy._build at 0x7fcf5c472830>", "forward": "<function ActorCriticPolicy.forward at 0x7fcf5c4728c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcf5c472950>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcf5c4729e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcf5c472a70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcf5c472b00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcf5c472b90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcf5c4be720>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651690616.387879, "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": 1272, "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-5.4.188+-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:d4b939937397b22ef3273b6445f2d37dc4d8060e39db55a8343fd07fba950b1d
-size 201341
+oid sha256:e215088c543017668a179b70a767d1cd79754928ff3dd148df138cde1c16f6c3
+size 188835

results.json

@@ -1 +1 @@
-{"mean_reward": 284.44583107950797, "std_reward": 12.531981857028008, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-04T18:31:04.010572"}
+{"mean_reward": 292.63209789655605, "std_reward": 17.52389699787343, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-04T19:09:56.890891"}