Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 273.15 +/- 22.21
+      value: 272.60 +/- 16.14
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
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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 0x7f438435fd90>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f438435fe20>", "reset_noise": 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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 0x7c50aab1ed40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c50aab1edd0>", "reset_noise": 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here refers to the model-free notion and should not\n    be used with the concept of rollout used in model-based RL or planning.\n    Hence, it is only involved in policy and value function training but not action selection.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param gae_lambda: Factor for trade-off of bias vs variance for Generalized Advantage Estimator\n        Equivalent to classic advantage when set to 1.\n    :param gamma: Discount factor\n    :param n_envs: Number of parallel environments\n    ", "__init__": "<function RolloutBuffer.__init__ at 0x7c50aacbcc10>", "reset": "<function RolloutBuffer.reset at 0x7c50aacbcca0>", "compute_returns_and_advantage": "<function RolloutBuffer.compute_returns_and_advantage at 0x7c50aacbcd30>", "add": "<function RolloutBuffer.add at 0x7c50aacbcdc0>", "get": "<function RolloutBuffer.get at 0x7c50aacbce50>", "_get_samples": "<function RolloutBuffer._get_samples at 0x7c50aacbcee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c50aacb2ec0>"}, "rollout_buffer_kwargs": {}, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": 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ppo-LunarLander-v2/_stable_baselines3_version

@@ -1 +1 @@
-2.0.0a5
+2.4.0a1

ppo-LunarLander-v2/data

@@ -4,29 +4,29 @@
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         "__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 0x7f438435fd90>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f438435fe20>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f438435feb0>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f438435ff40>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f4384360040>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f43843600d0>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4384360160>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f43843601f0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f4384360280>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4384360310>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f43843603a0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4384360430>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7c50aab1ed40>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c50aab1edd0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c50aab1ee60>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c50aab1eef0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7c50aab1ef80>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7c50aab1f010>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c50aab1f0a0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c50aab1f130>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7c50aab1f1c0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c50aab1f250>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c50aab1f2e0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c50aab1f370>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f438435a600>"
+        "_abc_impl": "<_abc._abc_data object at 0x7c50aab1ab00>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 2000896,
-    "_total_timesteps": 2000000,
-    "_num_timesteps_at_start": 0,
+    "num_timesteps": 3137536,
+    "_total_timesteps": 3136480,
+    "_num_timesteps_at_start": 2836480,
     "seed": null,
     "action_noise": null,
-    "start_time": 1717552456378719079,
+    "start_time": 1717564484052300930,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": null,
@@ -38,30 +38,30 @@
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     "use_sde": false,
     "sde_sample_freq": -1,
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     "_stats_window_size": 100,
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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
         ],
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-        "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.       ]",
+        "low": "[-1.5       -1.5       -5.        -5.        -3.1415927 -5.\n -0.        -0.       ]",
+        "high": "[1.5       1.5       5.        5.        3.1415927 5.        1.\n 1.       ]",
+        "low_repr": "[-1.5       -1.5       -5.        -5.        -3.1415927 -5.\n -0.        -0.       ]",
+        "high_repr": "[1.5       1.5       5.        5.        3.1415927 5.        1.\n 1.       ]",
         "_np_random": null
     },
     "action_space": {
@@ -74,23 +74,39 @@
         "_np_random": null
     },
     "n_envs": 1,
-    "n_steps": 1024,
+    "n_steps": 2048,
     "gamma": 0.999,
     "gae_lambda": 0.98,
     "ent_coef": 0.01,
-    "vf_coef": 0.5,
+    "vf_coef": 0.999,
     "max_grad_norm": 0.5,
+    "rollout_buffer_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVNgAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwNUm9sbG91dEJ1ZmZlcpSTlC4=",
+        "__module__": "stable_baselines3.common.buffers",
+        "__annotations__": "{'observations': <class 'numpy.ndarray'>, 'actions': <class 'numpy.ndarray'>, 'rewards': <class 'numpy.ndarray'>, 'advantages': <class 'numpy.ndarray'>, 'returns': <class 'numpy.ndarray'>, 'episode_starts': <class 'numpy.ndarray'>, 'log_probs': <class 'numpy.ndarray'>, 'values': <class 'numpy.ndarray'>}",
+        "__doc__": "\n    Rollout buffer used in on-policy algorithms like A2C/PPO.\n    It corresponds to ``buffer_size`` transitions collected\n    using the current policy.\n    This experience will be discarded after the policy update.\n    In order to use PPO objective, we also store the current value of each state\n    and the log probability of each taken action.\n\n    The term rollout here refers to the model-free notion and should not\n    be used with the concept of rollout used in model-based RL or planning.\n    Hence, it is only involved in policy and value function training but not action selection.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param gae_lambda: Factor for trade-off of bias vs variance for Generalized Advantage Estimator\n        Equivalent to classic advantage when set to 1.\n    :param gamma: Discount factor\n    :param n_envs: Number of parallel environments\n    ",
+        "__init__": "<function RolloutBuffer.__init__ at 0x7c50aacbcc10>",
+        "reset": "<function RolloutBuffer.reset at 0x7c50aacbcca0>",
+        "compute_returns_and_advantage": "<function RolloutBuffer.compute_returns_and_advantage at 0x7c50aacbcd30>",
+        "add": "<function RolloutBuffer.add at 0x7c50aacbcdc0>",
+        "get": "<function RolloutBuffer.get at 0x7c50aacbce50>",
+        "_get_samples": "<function RolloutBuffer._get_samples at 0x7c50aacbcee0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7c50aacb2ec0>"
+    },
+    "rollout_buffer_kwargs": {},
     "batch_size": 64,
     "n_epochs": 4,
     "clip_range": {
         ":type:": "<class 'function'>",
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"
     },
     "clip_range_vf": null,
     "normalize_advantage": true,
     "target_kl": null,
     "lr_schedule": {
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ppo-LunarLander-v2/policy.optimizer.pth

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ppo-LunarLander-v2/policy.pth

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+oid sha256:4eac64cad411f7859ebaa0fc8a110b8ca58bff7ff918072e6d24585117c7f5a6
 size 43762

ppo-LunarLander-v2/system_info.txt

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-- OS: Linux-5.4.0-169-generic-x86_64-with-glibc2.35 # 187-Ubuntu SMP Thu Nov 23 14:52:28 UTC 2023
-- Python: 3.10.12
-- Stable-Baselines3: 2.0.0a5
-- PyTorch: 2.2.0+cu121
+- OS: Linux-6.6.32-1-lts-x86_64-with-glibc2.39 # 1 SMP PREEMPT_DYNAMIC Sat, 25 May 2024 20:20:51 +0000
+- Python: 3.10.14
+- Stable-Baselines3: 2.4.0a1
+- PyTorch: 2.3.0+cu121
 - GPU Enabled: True
-- Numpy: 1.26.3
+- Numpy: 1.26.4
 - Cloudpickle: 3.0.0
-- Gymnasium: 0.28.1
+- Gymnasium: 0.29.1

results.json

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