1 million total steps, higher lr

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 232.31 +/- 23.66
+      value: 268.48 +/- 20.24
       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 0x7fcd44950950>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcd449509e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcd44950a70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcd44950b00>", "_build": "<function ActorCriticPolicy._build at 0x7fcd44950b90>", "forward": "<function ActorCriticPolicy.forward at 0x7fcd44950c20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcd44950cb0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcd44950d40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcd44950dd0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcd44950e60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcd44950ef0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcd4492c060>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652610545.9186769, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAI1Ber4R0TK9nVmlvM8fU7ull5s+X2gYPAAAgD8AAIA/Mzf5vEiZoroWGs45oJaNNUe37rriNu64AACAPwAAgD8apx0+vKd4PwGzhD6/utG+OJxNPk2IWT0AAAAAAAAAAOYk970g4Ys+WDPGvZuHG754iMS9vNAmvAAAAAAAAAAAMLiqviMhyj4Kh888TB3SvqVubD6ytEy9AAAAAAAAAACahAC91xNxuYD7FTtJMb81LQ0OvE7uMboAAIA/AACAPyZmJT4FAbW7sfOSOzMnXLk5kBW9mLI5ugAAgD8AAIA/82bIvh/C77ueeg24JnjgNVwpob2Ij0U3AACAPwAAgD9zGJO9Pap4OqVhwzuR5yo9mGzsO80nbz0AAAAAAAAAAJpvvLx7Pra6sVdEO6ZgmDZ1JX65vjRgugAAgD8AAIA/kxYVvoVXhLsCpTg7BUisOHHJyTzJtAK6AACAPwAAgD9mZaa99gRfuvZkgDoVTdA1kMwZujLflrkAAIA/AACAP1qVTr4qLtI+VU+zu/yqmb60B249ekZiPQAAAAAAAAAAM/+IOxTOkLoB7Jo67xF2NT+JJ7vUwLO5AACAPwAAgD/NDJS89rwxuj/ro7uDM504fbTJuv1iDjkAAIA/AACAP/NN+j2W/xo9qtPsvcZyi76UXtO92J9svQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": 124, "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"}}
+{"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 0x7ff721c937a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff721c93830>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff721c938c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff721c93950>", "_build": "<function ActorCriticPolicy._build at 0x7ff721c939e0>", "forward": "<function ActorCriticPolicy.forward at 0x7ff721c93a70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff721c93b00>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff721c93b90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff721c93c20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff721c93cb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff721c93d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff721c6a1e0>"}, "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": 32, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652617279.5659566, "learning_rate": {":type:": "<class 'function'>", ":serialized:": "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"}, "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="}, "_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": 124, "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"}}

ppo-LunarLander-v2-v3.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:028708c2a8120e5f0e01fbb257d6b2d4731c58dfec0f208362b5e21066b22133
+size 145122

ppo-LunarLander-v2-v3/_stable_baselines3_version

@@ -0,0 +1 @@
+1.5.0

ppo-LunarLander-v2-v3/data

@@ -0,0 +1,97 @@
+{
+    "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 0x7ff721c937a0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff721c93830>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff721c938c0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff721c93950>",
+        "_build": "<function ActorCriticPolicy._build at 0x7ff721c939e0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7ff721c93a70>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff721c93b00>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7ff721c93b90>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff721c93c20>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff721c93cb0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff721c93d40>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7ff721c6a1e0>"
+    },
+    "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": 32,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1652617279.5659566,
+    "learning_rate": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWV0AEAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsCS0NDDHwAZAEUAGQCFwBTAJRORz9QYk3S8an8Rz8aNuLrHEMth5QpjAF4lIWUjB48aXB5dGhvbi1pbnB1dC04LTYxNDAzZDQ4M2JkYj6UjAg8bGFtYmRhPpRLB0MAlCkpdJRSlH2UKIwLX19wYWNrYWdlX1+UTowIX19uYW1lX1+UjAhfX21haW5fX5R1Tk5OdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgXfZR9lChoFGgOjAxfX3F1YWxuYW1lX1+UaA6MD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBWMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UTowXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
+    },
+    "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="
+    },
+    "_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": 124,
+    "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
+}

ppo-LunarLander-v2-v3/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb452aa05a270dc639f84bb991be5d79716d3f93496c82e5dafc99f3b34528e1
+size 84829

ppo-LunarLander-v2-v3/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3b51fdc9b30b76a7381ca26dc473dbb397ab1c85179eec836db27ca2768ab9f5
+size 43201

ppo-LunarLander-v2-v3/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2-v3/system_info.txt

@@ -0,0 +1,7 @@
+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 sha256:26bf4e991059b92028a1554773e1c9134a0fd13684828afcf54929a5805fad6f
-size 222751
+oid sha256:83d3eaeb5ef76450d90e5f61943fe214936f9641ce3eace2f060ea42036809a0
+size 238286

results.json

@@ -1 +1 @@
-{"mean_reward": 232.30769382122685, "std_reward": 23.6631442031783, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-15T10:42:44.714362"}
+{"mean_reward": 268.4813107620365, "std_reward": 20.244163154165335, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-15T12:40:49.354642"}