commit with 10000000 iterations from unit1 notebook from local jupyterhub

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 260.93 +/- 79.13
+      value: 284.89 +/- 19.23
       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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f34e9a90430>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f34e9a904c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f34e9a90550>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f34e9a905e0>", "_build": "<function ActorCriticPolicy._build at 0x7f34e9a90670>", "forward": "<function ActorCriticPolicy.forward at 0x7f34e9a90700>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f34e9a90790>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f34e9a90820>", "_predict": "<function ActorCriticPolicy._predict at 0x7f34e9a908b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f34e9a90940>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f34e9a909d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f34e9a90a60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f34e9a91900>"}, "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": 524288, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679909406381825860, "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": -0.04857599999999995, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1488, "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": 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-5.14.0-239.el9.x86_64-x86_64-with-glibc2.34 # 1 SMP PREEMPT_DYNAMIC Thu Jan 19 14:14:19 UTC 2023", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu117", "GPU Enabled": "True", "Numpy": "1.24.1", "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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f34e9a90430>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f34e9a904c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f34e9a90550>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f34e9a905e0>", "_build": "<function ActorCriticPolicy._build at 0x7f34e9a90670>", "forward": "<function ActorCriticPolicy.forward at 0x7f34e9a90700>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f34e9a90790>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f34e9a90820>", "_predict": "<function ActorCriticPolicy._predict at 0x7f34e9a908b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f34e9a90940>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f34e9a909d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f34e9a90a60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f34e9a91900>"}, "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": 4521984, "_total_timesteps": 4500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679909965999650333, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAABAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 2592, "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": 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-5.14.0-239.el9.x86_64-x86_64-with-glibc2.34 # 1 SMP PREEMPT_DYNAMIC Thu Jan 19 14:14:19 UTC 2023", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu117", "GPU Enabled": "True", "Numpy": "1.24.1", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9bbce3021afa95f9abbaab700a6bb2c1d90a7857e3dbbcf03127be61f248a037
-size 147359
+oid sha256:937e0aa93552196b0d423b5fe3cb40dbabc80f41f625878b5e0c3609287ede8f
+size 147358

ppo-LunarLander-v2/data

@@ -43,12 +43,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 524288,
-    "_total_timesteps": 500000,
+    "num_timesteps": 4521984,
+    "_total_timesteps": 4500000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1679909406381825860,
+    "start_time": 1679909965999650333,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -57,26 +57,26 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAABAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
     },
     "_last_original_obs": null,
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.04857599999999995,
+    "_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": 1488,
+    "_n_updates": 2592,
     "n_steps": 2048,
     "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:fde9b8337bad7f82fa6dcc0c92deb4ac1c68cba4b392cba93e9c8d7d4aa32200
+oid sha256:cfb6765dff1d3f5ff66ad4935fdf4f35f28575b4c3a453c6fad3564a57dbf5e4
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1a12a3e35648901dd21c2ea8698d4db900b60703e61db99b5761ea23db412e46
+oid sha256:4ce5b81b23a1bcbe65b02d2efc2006243c8fab9679fe0b3897eac72d80406c42
 size 43393

results.json

@@ -1 +1 @@
-{"mean_reward": 260.9269124216416, "std_reward": 79.12976979910748, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-27T11:38:48.724696"}
+{"mean_reward": 284.88733765045424, "std_reward": 19.233407821038707, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-27T12:46:39.534834"}