Upload PPO LunarLander-v2 trained agent

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 22.42 +/- 147.19
+      value: 259.18 +/- 18.31
       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 0x7fe5d5797290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe5d5797320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe5d57973b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe5d5797440>", "_build": "<function ActorCriticPolicy._build at 0x7fe5d57974d0>", "forward": "<function ActorCriticPolicy.forward at 0x7fe5d5797560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe5d57975f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe5d5797680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe5d5797710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe5d57977a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe5d5797830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe5d57f00c0>"}, "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": 1665477609478772586, "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": 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-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.14", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+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 0x7fe5d5797290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe5d5797320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe5d57973b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe5d5797440>", "_build": "<function ActorCriticPolicy._build at 0x7fe5d57974d0>", "forward": "<function ActorCriticPolicy.forward at 0x7fe5d5797560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe5d57975f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe5d5797680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe5d5797710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe5d57977a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe5d5797830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe5d57f00c0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1665479936966057888, "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": 248, "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-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.14", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:79f0d3dec6cb83fc813427d7a7f5fa9b4277df35627e090dcdaa68d838e57fa1
-size 147150
+oid sha256:ed74d98981aa636d6df8ed0fee211f2a7c3253c751602f4f085270fd443b4a9d
+size 147152

ppo-LunarLander-v2/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 507904,
-    "_total_timesteps": 500000,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1665477609478772586,
+    "start_time": 1665479936966057888,
     "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:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAAAghTzhfIC62t2OOudXgTVvw8c5NNamuQAAgD8AAIA/zShAvlMyoz/Pxhm/kGX6vl/rob6D9/i+AAAAAAAAAABm7s49P7oOP2LIDb7nE3a+qxSnvEpDHL0AAAAAAAAAABqC8D3XD0i7SFcvvvC5UrwBqoU9ZBATvgAAgD8AAIA/zTCZu8RMnz7RX6I9/meAvlZpuDzYAag9AAAAAAAAAADNe+U8GJOsPbuTBLwNjVC+5uaTPaenoz0AAAAAAAAAADOumT32pBy6WpeEubwUBDOrWZG7ClubOAAAgD8AAIA/wFHOPUi3iroCkNg4sxzUMkYinbryevi3AACAPwAAgD9mmGu8e6yNujPnFrpDfNU13GIkO5H9LjkAAIA/AACAP3Nmtj0poHC6A9tCu5/vgDjM4ss6TdzTOQAAgD8AAIA/ZgYGvI/6JLrhHbU21xpYMukeaDubkta1AACAPwAAgD+NA8Y9e9yZukClFTpvmWA1aa8UO2k5K7kAAIA/AAAAALP0Az0pRCq6dDWgu1xZrDYpn7u7Uee5OgAAgD8AAIA/ZkmEPSmITLp2DU+54DsBtmk3Z7uDnHE4AACAPwAAgD9ztpQ9e7KKujSRjTvLhpW1vIirOpbxkrQAAIA/AACAPwCfX72IfLg/3mMQv5HCMz3Y6gO8eao9vgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -69,13 +69,13 @@
     "_current_progress_remaining": -0.015808000000000044,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "gAWVfhAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIMuNtpdfQZECUhpRSlIwBbJRN6AOMAXSUR0CRFoux8lXzdX2UKGgGaAloD0MIHhhA+NB5ZkCUhpRSlGgVTegDaBZHQJEZQOWjXWh1fZQoaAZoCWgPQwiOzCN/sNtmQJSGlFKUaBVN6ANoFkdAkR2LAP/aQHV9lChoBmgJaA9DCAYsuYrFMmFAlIaUUpRoFU3oA2gWR0CRJ1h60IC2dX2UKGgGaAloD0MIODC5UeSkY0CUhpRSlGgVTegDaBZHQJEt8+dK/VR1fZQoaAZoCWgPQwiKc9TRcfdiQJSGlFKUaBVN6ANoFkdAkS8dalk6LnV9lChoBmgJaA9DCFdbsb/snGVAlIaUUpRoFU3oA2gWR0CRNc8SPEKmdX2UKGgGaAloD0MIdR4V/3c1ZUCUhpRSlGgVTegDaBZHQJE2Ahib2Dh1fZQoaAZoCWgPQwjcD3hgAMFlQJSGlFKUaBVN6ANoFkdAkTeA3xWkrXV9lChoBmgJaA9DCJvLDYa6iWdAlIaUUpRoFU3oA2gWR0CROJ876pHadX2UKGgGaAloD0MIQznRrkIBZECUhpRSlGgVTegDaBZHQJE8OV5a/yp1fZQoaAZoCWgPQwgCvAUSlG5mQJSGlFKUaBVN6ANoFkdAkT0UNvwVkHV9lChoBmgJaA9DCE5iEFg5w2dAlIaUUpRoFU3oA2gWR0CRPXSpR4yHdX2UKGgGaAloD0MINCxGXevfZkCUhpRSlGgVTegDaBZHQJE/32EkB0Z1fZQoaAZoCWgPQwjb/L/qyI1jQJSGlFKUaBVN6ANoFkdAkVndGiHqNnV9lChoBmgJaA9DCHsS2JwD0WBAlIaUUpRoFU3oA2gWR0CRYI5OJtSAdX2UKGgGaAloD0MIcjEG1vHYYECUhpRSlGgVTegDaBZHQJFmxgfEGaB1fZQoaAZoCWgPQwjMCkW6n1ZhQJSGlFKUaBVN6ANoFkdAkWlCU1Q663V9lChoBmgJaA9DCFjjbDqCWmdAlIaUUpRoFU3oA2gWR0CRbPBtUGVzdX2UKGgGaAloD0MIxFxStd2YYkCUhpRSlGgVTegDaBZHQJF1WxbB42V1fZQoaAZoCWgPQwil12ZjpVlwQJSGlFKUaBVNDQNoFkdAkXWrOeJ53XV9lChoBmgJaA9DCPeUnBN7uGNAlIaUUpRoFU3oA2gWR0CRewJjDsMRdX2UKGgGaAloD0MI2PFfIAiCYECUhpRSlGgVTegDaBZHQJF8DIaLn9x1fZQoaAZoCWgPQwjK+s3E9C5jQJSGlFKUaBVN6ANoFkdAkYH12zOX3XV9lChoBmgJaA9DCDShSWLJG2RAlIaUUpRoFU3oA2gWR0CRg5i6QNkOdX2UKGgGaAloD0MIhh4xem7dYkCUhpRSlGgVTegDaBZHQJGEqyOaOPx1fZQoaAZoCWgPQwj59xkXDjtfQJSGlFKUaBVN6ANoFkdAkYhVJHy3C3V9lChoBmgJaA9DCGObVDTWJmNAlIaUUpRoFU3oA2gWR0CRiVVwxWT5dX2UKGgGaAloD0MIYLGGi9zkZECUhpRSlGgVTegDaBZHQJGJwCV8kUt1fZQoaAZoCWgPQwixTSoa64xhQJSGlFKUaBVN6ANoFkdAkYyEz9CNTHV9lChoBmgJaA9DCGwiMxc4f2JAlIaUUpRoFU3oA2gWR0CRpwevpyIYdX2UKGgGaAloD0MIlIeFWtNDYkCUhpRSlGgVTegDaBZHQJGtgvTPSlZ1fZQoaAZoCWgPQwjeyDzyB6xiQJSGlFKUaBVN6ANoFkdAkbO5MxoIwHV9lChoBmgJaA9DCFoQyvs4XEVAlIaUUpRoFUvRaBZHQJGzuwD/2kB1fZQoaAZoCWgPQwgpe0s5XyJnQJSGlFKUaBVN6ANoFkdAkbYitq59VnV9lChoBmgJaA9DCFlpUgq6S15AlIaUUpRoFU3oA2gWR0CRucp7TlT4dX2UKGgGaAloD0MImj474DosZECUhpRSlGgVTegDaBZHQJHB6tfXwsp1fZQoaAZoCWgPQwhqErwhjbJjQJSGlFKUaBVN6ANoFkdAkcI0HdGiH3V9lChoBmgJaA9DCGqHvybrr2VAlIaUUpRoFU3oA2gWR0CRx1uiN83NdX2UKGgGaAloD0MIjuczoN54YECUhpRSlGgVTegDaBZHQJHIVhgE2YR1fZQoaAZoCWgPQwhMM93rpNZiQJSGlFKUaBVN6ANoFkdAkc4cAJb+tXV9lChoBmgJaA9DCL99HThnpWdAlIaUUpRoFU3oA2gWR0CRz7FVDKHPdX2UKGgGaAloD0MIZ3+g3LYxY0CUhpRSlGgVTegDaBZHQJHQsskIHC51fZQoaAZoCWgPQwiobcMoiGViQJSGlFKUaBVN6ANoFkdAkdRK72+PBHV9lChoBmgJaA9DCJF8JZASuGRAlIaUUpRoFU3oA2gWR0CR1TM1CPZJdX2UKGgGaAloD0MIF4IclLAeZ0CUhpRSlGgVTegDaBZHQJHVm7Ackt51fZQoaAZoCWgPQwhCXaRQlgFnQJSGlFKUaBVN6ANoFkdAkdgwX/HYH3V9lChoBmgJaA9DCM6o+Sr5JEVAlIaUUpRoFUv9aBZHQJHavM4cWCV1fZQoaAZoCWgPQwi7C5QU2LpyQJSGlFKUaBVN8AFoFkdAkfSBcAzYVnV9lChoBmgJaA9DCFGjkGRWImRAlIaUUpRoFU3oA2gWR0CR97Cwr1/UdX2UKGgGaAloD0MIdCmuKnsacUCUhpRSlGgVTdcDaBZHQJH8QuctoSN1fZQoaAZoCWgPQwjvj/eqFXVnQJSGlFKUaBVN6ANoFkdAkf07r9l2/3V9lChoBmgJaA9DCGIwf4VMMGlAlIaUUpRoFU3oA2gWR0CR/44dIXj3dX2UKGgGaAloD0MIrFPle0bmYkCUhpRSlGgVTegDaBZHQJIDdKCg9Nh1fZQoaAZoCWgPQwjHYwYq4/xlQJSGlFKUaBVN6ANoFkdAkgxtCE6DG3V9lChoBmgJaA9DCJwYkpMJnGVAlIaUUpRoFU3oA2gWR0CSDLtfoicHdX2UKGgGaAloD0MIyAvp8BCEQkCUhpRSlGgVTQABaBZHQJIMvZezD4x1fZQoaAZoCWgPQwie0sH6vyRiQJSGlFKUaBVN6ANoFkdAkhN3erMkhXV9lChoBmgJaA9DCLPviuD/WmJAlIaUUpRoFU3oA2gWR0CSG4DVH4GmdX2UKGgGaAloD0MILGUZ4liybECUhpRSlGgVTZcDaBZHQJIb+IDYAbR1fZQoaAZoCWgPQwjAkxYuq9dnQJSGlFKUaBVN6ANoFkdAkhyjEehf0HV9lChoBmgJaA9DCMx7nGnCYmRAlIaUUpRoFU3oA2gWR0CSIVlVtGd7dX2UKGgGaAloD0MIP3RBfUv+YkCUhpRSlGgVTegDaBZHQJIhyHxjJ+51fZQoaAZoCWgPQwgV/aGZJ4JjQJSGlFKUaBVN6ANoFkdAkiSdFz+3pnV9lChoBmgJaA9DCNVcbjBUpWBAlIaUUpRoFU3oA2gWR0CSJ2PWQOnVdX2UKGgGaAloD0MIGJmAXyOYYUCUhpRSlGgVTegDaBZHQJJBZNg0CRx1fZQoaAZoCWgPQwhMF2L1x91mQJSGlFKUaBVN6ANoFkdAkkSHARChOHV9lChoBmgJaA9DCN8yp8vib25AlIaUUpRoFU2xAWgWR0CSRpiExqO+dX2UKGgGaAloD0MI2CrB4nCOZ0CUhpRSlGgVTegDaBZHQJJItHrhR651fZQoaAZoCWgPQwjNrKWANIxjQJSGlFKUaBVN6ANoFkdAkkt7YkE9uHV9lChoBmgJaA9DCBDM0eN3TGhAlIaUUpRoFU3oA2gWR0CSToeZ5Rj0dX2UKGgGaAloD0MI+mGE8OiuZECUhpRSlGgVTegDaBZHQJJVmm65Gz91fZQoaAZoCWgPQwj+RGXDmoxlQJSGlFKUaBVN6ANoFkdAklXcxj8UEnV9lChoBmgJaA9DCM138BOHwWFAlIaUUpRoFU3oA2gWR0CSVd5YYBNmdX2UKGgGaAloD0MIZW6+Ed0lYUCUhpRSlGgVTegDaBZHQJJbdhmXgLt1fZQoaAZoCWgPQwiOWmH6XgNgQJSGlFKUaBVN6ANoFkdAkmKoE0SAY3V9lChoBmgJaA9DCHFxVG4igWZAlIaUUpRoFU3oA2gWR0CSY7qCpWFOdX2UKGgGaAloD0MIR+f8FEdaYkCUhpRSlGgVTegDaBZHQJJofcvduYR1fZQoaAZoCWgPQwj7dac7z1pkQJSGlFKUaBVN6ANoFkdAkmjxoh6jWXV9lChoBmgJaA9DCLeb4JsmPmZAlIaUUpRoFU3oA2gWR0CSa8om5UcXdX2UKGgGaAloD0MI8+SaApnbZUCUhpRSlGgVTegDaBZHQJJuqgte2NN1fZQoaAZoCWgPQwhxOslWlyFIQJSGlFKUaBVL5mgWR0CSbvssxwhodX2UKGgGaAloD0MIt0YE4+CGYkCUhpRSlGgVTegDaBZHQJJ0+S/0ulJ1fZQoaAZoCWgPQwgNVTGV/iVvQJSGlFKUaBVNVgFoFkdAkommrsByS3V9lChoBmgJaA9DCBJKXwi53mZAlIaUUpRoFU3oA2gWR0CSi6uGbkOqdX2UKGgGaAloD0MIKSMuAA3KYUCUhpRSlGgVTegDaBZHQJKNvRiPQv91fZQoaAZoCWgPQwjy6hwDsvtjQJSGlFKUaBVN6ANoFkdAko/2nXNC7nV9lChoBmgJaA9DCC52+6wylWVAlIaUUpRoFU3oA2gWR0CSkv4HX2/SdX2UKGgGaAloD0MIqU9yh03uZECUhpRSlGgVTegDaBZHQJKWYK+i8Fp1fZQoaAZoCWgPQwjs98Q61TRlQJSGlFKUaBVN6ANoFkdAkp6LofSx7nV9lChoBmgJaA9DCD8buW7K4mJAlIaUUpRoFU3oA2gWR0CSnthYNiH7dX2UKGgGaAloD0MIjnVxG43BZkCUhpRSlGgVTegDaBZHQJKe24PPLPl1fZQoaAZoCWgPQwiu8C4XcRlkQJSGlFKUaBVN6ANoFkdAkqU6VD8cdnV9lChoBmgJaA9DCCMShZb10WJAlIaUUpRoFU3oA2gWR0CSsvOI68xsdX2UKGgGaAloD0MIVoFaDB7JXUCUhpRSlGgVTegDaBZHQJKzbNmlImR1fZQoaAZoCWgPQwhEbLBwEs1iQJSGlFKUaBVN6ANoFkdAkrZDxkNF0HV9lChoBmgJaA9DCHIVi9+Un2ZAlIaUUpRoFU3oA2gWR0CSuO0/nnuBdX2UKGgGaAloD0MIQZyHExjmY0CUhpRSlGgVTegDaBZHQJK5Nul41P51fZQoaAZoCWgPQwiy2ZHqO7xhQJSGlFKUaBVN6ANoFkdAkr6pHVf/m3V9lChoBmgJaA9DCBu5bkr582ZAlIaUUpRoFU3oA2gWR0CSv45qdpZfdWUu"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 124,
+    "_n_updates": 248,
     "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 sha256:2ae5689046fe64077a98f3f61f9e22768303fcb5c986c73f16e0f81b0798ab7e
+oid sha256:bdc41101188cb5f5da7e1c4ce7f179bbf4cca5c9bf806f61fd408fb6b6da165f
 size 87865

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:dc9a5c8c6516cb5d16d66bea6c3a8e87f0cba179a0386ce37de8f51ac63034cd
+oid sha256:3f418a4894d33de24454fd87d18743ef54fe5b2e8339cf48198d15103e020a8b
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": 22.416691547244803, "std_reward": 147.19368762032246, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-11T09:04:22.917557"}
+{"mean_reward": 259.17994089090223, "std_reward": 18.31312165415974, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-11T09:40:06.629818"}