Just a quick test

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -133.27 +/- 135.76
+      value: 264.24 +/- 24.36
       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 0x7f7f3aa9a050>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7f3aa9a0e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7f3aa9a170>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7f3aa9a200>", "_build": "<function ActorCriticPolicy._build at 0x7f7f3aa9a290>", "forward": "<function ActorCriticPolicy.forward at 0x7f7f3aa9a320>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7f3aa9a3b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7f3aa9a440>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7f3aa9a4d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7f3aa9a560>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7f3aa9a5f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7f3aa9a680>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f7f3aa3b300>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 16384, "_total_timesteps": 100, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1698119147520981603, "learning_rate": 0.0003, "tensorboard_log": null, "_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": -162.84, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 4, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
+{"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 0x7f7f3aa9a050>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7f3aa9a0e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7f3aa9a170>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7f3aa9a200>", "_build": "<function ActorCriticPolicy._build at 0x7f7f3aa9a290>", "forward": "<function ActorCriticPolicy.forward at 0x7f7f3aa9a320>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7f3aa9a3b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7f3aa9a440>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7f3aa9a4d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7f3aa9a560>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7f3aa9a5f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7f3aa9a680>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f7f3aa3b300>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1698119485142363184, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 252, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:eecc95cd2122e0c2b1093ea9c92902d56bc74b6072c4c2d72d2abfa789173535
-size 147900
+oid sha256:b54b2e4656164a215950a0cdb7e28f1d7b72eacc34b37eadd6a7bdf28ecaadc1
+size 147998

ppo-LunarLander-v2/data

@@ -21,17 +21,17 @@
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 16384,
-    "_total_timesteps": 100,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1698119147520981603,
+    "start_time": 1698119485142363184,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -41,17 +41,17 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -162.84,
+    "_current_progress_remaining": -0.015808000000000044,
     "_stats_window_size": 100,
     "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": 4,
+    "_n_updates": 252,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:88a67938f926396639eeb3aa602c61aa17b1ccf50514fce67ecb1fa872f22ee0
+oid sha256:edbb345e362684daeb3a36c26ee82df8fdb7ce5c5f0e5ff8378fa53c82523e93
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b5183089d078ebde6bc241f67874c824b868c8055cceac29e2d6da7779f60b66
+oid sha256:5bfa7a9d46d8579ca520226a48b7e1b2d75cf8c58a082a3f84b39526ce65e363
 size 43762

results.json

@@ -1 +1 @@
-{"mean_reward": -133.26603459999998, "std_reward": 135.762234637538, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-24T03:49:56.590654"}
+{"mean_reward": 264.24240810000003, "std_reward": 24.36008360463322, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-24T04:13:54.597493"}