commit with 20 000 000 iterations from unit1 notebook from local jupyterhub

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 302.89 +/- 13.61
+      value: 294.24 +/- 15.86
       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:": "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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": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679916065274815029, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAADMj9Tt71oe66FoxM+kpH7DV9WY5cyPAswAAgD8AAIA/ZmIFvEghhLreAk06wFXeNez7GDvyXG65AACAPwAAgD8zSgy9lgCYP7KFir35Q0O/kBh+veJ92b0AAAAAAAAAALN5HT1n5AS9I4MKvvbnB7w7Hws9engkPgAAgD8AAIA/AODQOh9x4Lv1TDc+QlylPILNIjxzaoA7AACAPwAAgD86nVI+/ruDPwgzgz4Ta/e+L1L/PhELnz4AAAAAAAAAABpPWj1PgQc9EwyOvnQsqL7p0iC+2FFGvgAAAAAAAAAAZr20PKmHM7zS9oq9putUPX5moj22eCs8AACAPwAAgD+a59Q84cCfuuYZezkG3Ws06fqEue6OkLgAAIA/AACAP9pQpr1rv3k/CIwTvjuxhr8s7UK+g+dpvQAAAAAAAAAAmh0VPI/qfLqai3O2+tNYsQLDCLtMF5Q1AACAPwAAgD+mP7Q97bi4P2bG1z7lPhm+ky81PpOF2j4AAAAAAAAAAJOvFT4PuqQ/lkMPP7Do+b7uE3k+rcj6PgAAAAAAAAAAM5jtPBQil7ruUOg3k/vPMpWq+LrmVQa3AACAPwAAgD9tADc+A3T9Ph+bSr7RlU2/jxCdPsMBsb4AAAAAAAAAAGY32Lyqc/E+4fmUukHHVb+03xe9T5gCvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3584, "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": 6029312, "_total_timesteps": 6000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679918589547292110, "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": 5056, "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 sha256:3559f118b528db3b869867d8f745880cc84832886c53a31943c18813e0944a70
+oid sha256:0c63be334d33895db57e738cf8af6e8c9e4e11e37a30b6a696f55305a83e1e3a
 size 147358

ppo-LunarLander-v2/data

@@ -43,12 +43,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 2031616,
-    "_total_timesteps": 2000000,
+    "num_timesteps": 6029312,
+    "_total_timesteps": 6000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1679916065274815029,
+    "start_time": 1679918589547292110,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -57,7 +57,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -67,16 +67,16 @@
     "_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": 3584,
+    "_n_updates": 5056,
     "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:cb7622f9fcfaec808b91be13188f9653d78d40ee80148afbbd7ccc1a326ce8be
+oid sha256:2eb37c4587fdaa06dd167b716af7d892a5bb042b06361d4eb4c6e4396516bf8f
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:49e43b84a826aa7b33846f2f01a181004097629c5ad8488f287d95b9dd1fcc5c
+oid sha256:b670de748945eb6ccccbe6d23ca430fad82d7fe704ae1b9456127a5c4cd29f7c
 size 43393

results.json

@@ -1 +1 @@
-{"mean_reward": 302.89234714563696, "std_reward": 13.610120507641433, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-27T14:02:00.993718"}
+{"mean_reward": 294.2398183799918, "std_reward": 15.855787263111411, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-27T15:44:12.690259"}