Upload model: PPO-LunarLander-v2, version: 8.000000

PPO-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bde84d0e8f058f9a045039c9743e0c7584740f50c35d0c5b41f313bc5162f9c0
-size 143983
+oid sha256:6b4d07ba2e4fbc6f60bf309260fff5b45c41ea034a20acffaf1d47b356c368c8
+size 143987

PPO-LunarLander-v2/data

@@ -4,19 +4,19 @@
         ":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 0x7f461bcfd170>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f461bcfd200>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f461bcfd290>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f461bcfd320>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f461bcfd3b0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f461bcfd440>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f461bcfd4d0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f461bcfd560>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f461bcfd5f0>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f461bcfd680>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f461bcfd710>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7fdc8ed5cd40>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fdc8ed5cdd0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fdc8ed5ce60>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fdc8ed5cef0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fdc8ed5cf80>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fdc8ed62050>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fdc8ed620e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fdc8ed62170>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fdc8ed62200>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fdc8ed62290>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fdc8ed62320>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f461bd57060>"
+        "_abc_impl": "<_abc_data object at 0x7fdc8edae570>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 2015232,
+    "_total_timesteps": 2000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1651784247.5355902,
+    "start_time": 1651840369.2020814,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,16 +66,16 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.015808000000000044,
+    "_current_progress_remaining": -0.007616000000000067,
     "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": 1520,
+    "_n_updates": 1764,
     "n_steps": 1024,
     "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:b397c1db0b58cafde47645159d1e7ad965630778ebe17603133a355346a53096
+oid sha256:88a8b9b7698de5120c9a221af3e4bb2a67f28648b7255679136cee80986f0a69
 size 84893

PPO-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0248e44f6437452d09c783f43f3823104de2ac7cc0454145264325e58bd53d64
+oid sha256:79026141e2f916467fd3c49a8ef615d2d54c75926c5896b309da614030f18954
 size 43201

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 291.64 +/- 18.85
+      value: 279.83 +/- 17.31
       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 0x7f461bcfd170>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f461bcfd200>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f461bcfd290>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f461bcfd320>", "_build": "<function ActorCriticPolicy._build at 0x7f461bcfd3b0>", "forward": "<function ActorCriticPolicy.forward at 0x7f461bcfd440>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f461bcfd4d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f461bcfd560>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f461bcfd5f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f461bcfd680>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f461bcfd710>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f461bd57060>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651784247.5355902, "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": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1520, "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 0x7fdc8ed5cd40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fdc8ed5cdd0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fdc8ed5ce60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fdc8ed5cef0>", "_build": "<function ActorCriticPolicy._build at 0x7fdc8ed5cf80>", "forward": "<function ActorCriticPolicy.forward at 0x7fdc8ed62050>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fdc8ed620e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fdc8ed62170>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fdc8ed62200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fdc8ed62290>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fdc8ed62320>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fdc8edae570>"}, "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": 2015232, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651840369.2020814, "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": -0.007616000000000067, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIl6yKcBPWcUCUhpRSlIwBbJRLxowBdJRHQKOFdoZAIIF1fZQoaAZoCWgPQwgQdopVQ+txQJSGlFKUaBVLtWgWR0CjhZF/pdKNdX2UKGgGaAloD0MIXrpJDAKSUkCUhpRSlGgVS4poFkdAo4YaYRdyDXV9lChoBmgJaA9DCL4tWKrLkXJAlIaUUpRoFUu2aBZHQKOGIPvKEFp1fZQoaAZoCWgPQwiFRNrGn2RyQJSGlFKUaBVLrWgWR0CjhkNG3F1kdX2UKGgGaAloD0MI01CjkCSkc0CUhpRSlGgVS9xoFkdAo4ZBQ1rIo3V9lChoBmgJaA9DCN/BTxxANXRAlIaUUpRoFUvBaBZHQKOGhHd43WF1fZQoaAZoCWgPQwibVDTWvglzQJSGlFKUaBVLrmgWR0Cjhp+Wv8qGdX2UKGgGaAloD0MIswsG1xzEckCUhpRSlGgVS6loFkdAo4bXv0AcUHV9lChoBmgJaA9DCDSg3oxapXBAlIaUUpRoFUueaBZHQKOHQ12JSBN1fZQoaAZoCWgPQwiUiVsFsapyQJSGlFKUaBVLvGgWR0Cjh0HRTjvNdX2UKGgGaAloD0MIc9cS8kHacUCUhpRSlGgVS75oFkdAo4ePx8UmD3V9lChoBmgJaA9DCCJVFK8yc3FAlIaUUpRoFUvKaBZHQKOHlW1+iJx1fZQoaAZoCWgPQwjWpxyTxT0+QJSGlFKUaBVLY2gWR0Cjh6OgpSaWdX2UKGgGaAloD0MIqYO8HsxkckCUhpRSlGgVS75oFkdAo4fCqXF98nV9lChoBmgJaA9DCGVR2EURHHBAlIaUUpRoFUu6aBZHQKOIBBlcyFh1fZQoaAZoCWgPQwiun/6z5olxQJSGlFKUaBVLu2gWR0CjiCQ+lj3FdX2UKGgGaAloD0MIcTyfAXVlc0CUhpRSlGgVS8FoFkdAo5dbSLIgeXV9lChoBmgJaA9DCBrggmzZRXNAlIaUUpRoFUvGaBZHQKOXdSiM5wR1fZQoaAZoCWgPQwgXEcXkDaVvQJSGlFKUaBVLrWgWR0Cjl4aOYIBzdX2UKGgGaAloD0MI6nsNwTHXcECUhpRSlGgVS6doFkdAo5eNYp2ECnV9lChoBmgJaA9DCFDkSdK1l3NAlIaUUpRoFUvFaBZHQKOXlctXgcd1fZQoaAZoCWgPQwgfaXBbG65yQJSGlFKUaBVLlGgWR0CjmElCTlkpdX2UKGgGaAloD0MIFAZlGk1edECUhpRSlGgVS9BoFkdAo5hcJx//enV9lChoBmgJaA9DCK5kx0agDGVAlIaUUpRoFU3oA2gWR0CjmKzspobodX2UKGgGaAloD0MI1pC4xxK+c0CUhpRSlGgVS85oFkdAo5i/tMPBi3V9lChoBmgJaA9DCLiumBEeD3JAlIaUUpRoFUvPaBZHQKOYx3/xUed1fZQoaAZoCWgPQwg26bZELhdxQJSGlFKUaBVLumgWR0CjmMauwHJLdX2UKGgGaAloD0MIWUxsPi55c0CUhpRSlGgVS8loFkdAo5j5yhi9ZnV9lChoBmgJaA9DCOf7qfHSZ3JAlIaUUpRoFUu/aBZHQKOZPhoduHh1fZQoaAZoCWgPQwjWbrvQ3ExyQJSGlFKUaBVLuGgWR0CjmUSzw+dLdX2UKGgGaAloD0MIp+fdWBCfc0CUhpRSlGgVS+ZoFkdAo5mFMAWBSXV9lChoBmgJaA9DCEnVdhO8ZHBAlIaUUpRoFUujaBZHQKOZlrKvFFV1fZQoaAZoCWgPQwhzY3rCkp1wQJSGlFKUaBVLo2gWR0CjmazdDYywdX2UKGgGaAloD0MIzm4tkyEackCUhpRSlGgVS7toFkdAo5oH5nDiwXV9lChoBmgJaA9DCHTQJRw6/3BAlIaUUpRoFUu4aBZHQKOaC4vN/vx1fZQoaAZoCWgPQwhYqgt4WU5zQJSGlFKUaBVLwWgWR0CjmiEUTL4fdX2UKGgGaAloD0MICoUIOESMcUCUhpRSlGgVS7poFkdAo5rKqp97W3V9lChoBmgJaA9DCMCTFi6r0HFAlIaUUpRoFUvGaBZHQKOa5B3zMA51fZQoaAZoCWgPQwj3yOaqeblxQJSGlFKUaBVLqmgWR0Cjmy0AtFrmdX2UKGgGaAloD0MI3/5cNOSwcUCUhpRSlGgVS75oFkdAo5s0xASnL3V9lChoBmgJaA9DCMAma9QDsnJAlIaUUpRoFUvCaBZHQKObSD5CWu51fZQoaAZoCWgPQwjlX8sr1wZyQJSGlFKUaBVLyGgWR0Cjm0Z4Oc2BdX2UKGgGaAloD0MIX10VqMVAc0CUhpRSlGgVS8hoFkdAo5tbI91U2nV9lChoBmgJaA9DCGajc37KqnBAlIaUUpRoFUuvaBZHQKObhtgrpaB1fZQoaAZoCWgPQwiIn/8ePBd0QJSGlFKUaBVLs2gWR0Cjm5kZR8+idX2UKGgGaAloD0MI02uzsdI8cECUhpRSlGgVS69oFkdAo5vGdiDujXV9lChoBmgJaA9DCFjLnZkg53FAlIaUUpRoFUu6aBZHQKOcE1og3cZ1fZQoaAZoCWgPQwhSgZNtIBNyQJSGlFKUaBVLpWgWR0CjnCtuUD+zdX2UKGgGaAloD0MIKUAUzJhrckCUhpRSlGgVS9FoFkdAo5xKSJTESHV9lChoBmgJaA9DCMzR4/d2InBAlIaUUpRoFUu4aBZHQKOcc0WuX/p1fZQoaAZoCWgPQwhffNEer3hyQJSGlFKUaBVLxWgWR0CjnLTot+TedX2UKGgGaAloD0MIbLJGPcSycECUhpRSlGgVS7xoFkdAo51emgrYoXV9lChoBmgJaA9DCB6HwfxVxHFAlIaUUpRoFUuvaBZHQKOdnlhgE2Z1fZQoaAZoCWgPQwhrEVFMXo5zQJSGlFKUaBVL12gWR0CjnayxZ+x4dX2UKGgGaAloD0MI0LTEymhfckCUhpRSlGgVS59oFkdAo52/kWAPNHV9lChoBmgJaA9DCKc9JeeEcnNAlIaUUpRoFUvAaBZHQKOdyKrJbMZ1fZQoaAZoCWgPQwhIFjCB21RzQJSGlFKUaBVLxGgWR0Cjnc82rGR3dX2UKGgGaAloD0MIlrN3RltMckCUhpRSlGgVS6xoFkdAo53YSg5BC3V9lChoBmgJaA9DCEBrfvyljXRAlIaUUpRoFUu7aBZHQKOd3Z8KG+N1fZQoaAZoCWgPQwgAV7JjI15yQJSGlFKUaBVLxGgWR0CjneW0iQkpdX2UKGgGaAloD0MItJPBUbKockCUhpRSlGgVS9VoFkdAo56c65oXbnV9lChoBmgJaA9DCO86G/KP8nFAlIaUUpRoFUu4aBZHQKOeo0Sh8IB1fZQoaAZoCWgPQwiY9zjTRO9yQJSGlFKUaBVLyGgWR0CjnsTIV/MGdX2UKGgGaAloD0MI/fm2YCmscUCUhpRSlGgVS7BoFkdAo57Q9vCMxXV9lChoBmgJaA9DCNOE7ScjSnNAlIaUUpRoFUvLaBZHQKOfBV4oqkN1fZQoaAZoCWgPQwhPsWoQJlBwQJSGlFKUaBVLuGgWR0CjnzD0UXYUdX2UKGgGaAloD0MIrFJ6ppcJckCUhpRSlGgVS7toFkdAo5/vB55Z83V9lChoBmgJaA9DCHJTA81nw2dAlIaUUpRoFU3oA2gWR0CjoCgvcrRTdX2UKGgGaAloD0MIhbLw9TWccUCUhpRSlGgVS7doFkdAo6A8ERrad3V9lChoBmgJaA9DCGIwf4WM+nJAlIaUUpRoFUvCaBZHQKOgQ+BYmsx1fZQoaAZoCWgPQwiwx0RKM+VzQJSGlFKUaBVLwWgWR0CjoEz4L1EmdX2UKGgGaAloD0MIvM6G/DPVcUCUhpRSlGgVS7poFkdAo6BO4Vh1DHV9lChoBmgJaA9DCLIqwk2GEXNAlIaUUpRoFUvGaBZHQKOgeFlCkXV1fZQoaAZoCWgPQwjZXDXPEa1xQJSGlFKUaBVLv2gWR0CjoHiZWq95dX2UKGgGaAloD0MIr5l8s80Fc0CUhpRSlGgVS8poFkdAo6CMfRu0kXV9lChoBmgJaA9DCECH+fKCPXNAlIaUUpRoFUvTaBZHQKOgqTewcHZ1fZQoaAZoCWgPQwh9ryE4rmpyQJSGlFKUaBVLlGgWR0CjoRix3V0+dX2UKGgGaAloD0MIkGrY78kKcUCUhpRSlGgVS7RoFkdAo6EbrkbPyHV9lChoBmgJaA9DCAWJ7e4B9HFAlIaUUpRoFUu9aBZHQKOhHAeJYT11fZQoaAZoCWgPQwijHTf8LrxyQJSGlFKUaBVLs2gWR0CjoSI11nuidX2UKGgGaAloD0MIuVLPglC5cUCUhpRSlGgVS8xoFkdAo6FCrBCUo3V9lChoBmgJaA9DCBy0Vx9PeHFAlIaUUpRoFUvJaBZHQKOhmA93bEh1fZQoaAZoCWgPQwiRgTy7fJZxQJSGlFKUaBVLmWgWR0CjohuqFRHgdX2UKGgGaAloD0MIqtbCLLTEcUCUhpRSlGgVS8loFkdAo6JnfXPJJXV9lChoBmgJaA9DCLDmAMEcxHFAlIaUUpRoFUvBaBZHQKOifyo4uK51fZQoaAZoCWgPQwhs0Jfevv9wQJSGlFKUaBVLumgWR0CjooKXfIjodX2UKGgGaAloD0MITS7GwLrkckCUhpRSlGgVS7doFkdAo6Kyp1ie/nV9lChoBmgJaA9DCHqrrkO1VHBAlIaUUpRoFUuzaBZHQKOivJ6IFeR1fZQoaAZoCWgPQwj5SEp6mHtyQJSGlFKUaBVLu2gWR0CjosMFlkH2dX2UKGgGaAloD0MIf/s6cI7ickCUhpRSlGgVS8toFkdAo6LJ8QZn+XV9lChoBmgJaA9DCGGMSBSa4XFAlIaUUpRoFUuwaBZHQKOi1y8zyjJ1fZQoaAZoCWgPQwi2EyUhURRyQJSGlFKUaBVL12gWR0Cjot3J5mh/dX2UKGgGaAloD0MIJGJKJFFGcUCUhpRSlGgVS61oFkdAo6NBy+6AfHV9lChoBmgJaA9DCILix5j7f3FAlIaUUpRoFUu+aBZHQKOjfQY1pCd1fZQoaAZoCWgPQwhkzF1LiM1zQJSGlFKUaBVLwWgWR0Cjo4Pv0AcUdX2UKGgGaAloD0MIEodsIJ1QcUCUhpRSlGgVS8ZoFkdAo6PMZWJaaHV9lChoBmgJaA9DCPSG+8ht6HNAlIaUUpRoFUvUaBZHQKOj1hw2l2x1fZQoaAZoCWgPQwjxun7Bbi5MQJSGlFKUaBVLWWgWR0Cjo+cIAwPAdX2UKGgGaAloD0MIwmosYa3BcUCUhpRSlGgVS7ZoFkdAo6Pw7/4qPXVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1764, "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"}}

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c14c1538060ce57071ada5f9afc4819e12f1f27f5368f5dc1f4311ab13f087dc
-size 178714
+oid sha256:a8e7f1298be6f47d27b5d1e2dafda934e95defc0a412970f51449d0ae29f53cf
+size 180997

results.json

@@ -1 +1 @@
-{"mean_reward": 291.6447496529725, "std_reward": 18.851853542081287, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-05T21:14:10.174980"}
+{"mean_reward": 279.82561914139467, "std_reward": 17.3087147319887, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-06T13:03:30.456410"}