first trained model uploaded!

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 266.12 +/- 36.06
+      value: 276.78 +/- 23.02
       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 0x7f5ce0877b50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5ce0877be0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5ce0877c70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5ce0877d00>", "_build": "<function ActorCriticPolicy._build at 0x7f5ce0877d90>", "forward": "<function ActorCriticPolicy.forward at 0x7f5ce0877e20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f5ce0877eb0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5ce0877f40>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5ce0880040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5ce08800d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5ce0880160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5ce08801f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f5ce0a04500>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 100352, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1720964562500669819, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAADMC8LwuHc89VKEavsJgZ74oU/C8hOUdvAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "_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": 5870, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "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 0x7f5ce0877b50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5ce0877be0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5ce0877c70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5ce0877d00>", "_build": "<function ActorCriticPolicy._build at 0x7f5ce0877d90>", "forward": "<function ActorCriticPolicy.forward at 0x7f5ce0877e20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f5ce0877eb0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5ce0877f40>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5ce0880040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5ce08800d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5ce0880160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5ce08801f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f5ce0a04500>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 100352, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1720964969937371480, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAGaWoLoUJIa6kKcrNQYiZDACSyk5UFxgtAAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "_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": 6360, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "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 sha256:470615dc5028b49d2a7c39ece8033bf85457edb1fe0e8a424b698de4efc816f0
-size 147326
+oid sha256:34d36133bfab69012900c0580f33eec299ec57e6be334427efdc8ace427c2d81
+size 147318

ppo-LunarLander-v2/data

@@ -26,12 +26,12 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1720964562500669819,
+    "start_time": 1720964969937371480,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAADMC8LwuHc89VKEavsJgZ74oU/C8hOUdvAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAGaWoLoUJIa6kKcrNQYiZDACSyk5UFxgtAAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -45,13 +45,13 @@
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "gAWV9AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQG+X8jiXIEOMAWyUS+SMAXSUR0CzB1k/r0J4dX2UKGgGR0Bx43BxgiNbaAdL7GgIR0CzB6/9Hc1wdX2UKGgGR0BhXswztTkyaAdN6ANoCEdAswqa2TgVGnV9lChoBkdAc0qIIF/x2GgHS9JoCEdAswsEy0rsjXV9lChoBkdAcM0ZQHiWFGgHS+ZoCEdAswttV6u4gHV9lChoBkdAc7VXmeUY9GgHTRQBaAhHQLML9FuejEh1fZQoaAZHQHMEA7tAs05oB00QAWgIR0CzDH85XEIgdX2UKGgGR0ByQRPl+3H8aAdL22gIR0CzDPbMPjGUdX2UKGgGR0BxgmdupCKKaAdL0WgIR0CzDUsLSeAedX2UKGgGR0BxEObb1yvLaAdL9mgIR0CzDaMw5/9YdX2UKGgGR0BjAmvB7/n4aAdN6ANoCEdAsxCX3JxNqXV9lChoBkdAcr4C0WuX/2gHS/doCEdAsxDx/CqIanV9lChoBkdAccl8FpwjuGgHS+RoCEdAsxFFzp5eJHV9lChoBkdAcewKA8Swn2gHS8hoCEdAsxGNLAYYSHV9lChoBkdAcNTnP3SKFmgHS+poCEdAsxHg+GGmDXV9lChoBkdAcoUo86mwaGgHS9VoCEdAsxOiTpxFRnV9lChoBkdAcMmJ8v24/mgHS/FoCEdAsxP7eFcps3V9lChoBkdAcGnza9K28mgHS+ZoCEdAsxRQS26TXHV9lChoBkdAcER1qFh5PmgHS8ZoCEdAsxSYYTCcgHV9lChoBkdAcKSfm9xp+WgHS9ZoCEdAsxTlkAggYHV9lChoBkdAclloc7yQP2gHS/doCEdAsxVCU8mrsHV9lChoBkdAcR2iBGx2S2gHS8FoCEdAsxWHY5DJEHV9lChoBkdAcR4SvTw2EWgHS+hoCEdAsxXaf029+XV9lChoBkdAcXkF+/gzg2gHTX0CaAhHQLMYnZGKAJ91fZQoaAZHQG8pXVbzK9xoB0vOaAhHQLMZCbg0j1R1fZQoaAZHQHOdp1vES/VoB0v8aAhHQLMZilQMx491fZQoaAZHQHGWghr30wtoB0vjaAhHQLMZ9UoKD011fZQoaAZHQHB7ws052hZoB00CAWgIR0CzGlJbpu/DdX2UKGgGR0Bw4O4y44IbaAdL4WgIR0CzGqInOSntdX2UKGgGR0BxZAuvllshaAdL52gIR0CzGvizLOiWdX2UKGgGR0By2ucvugHvaAdNCgFoCEdAsxtahM8HOnV9lChoBkdAcUCfbKzRhWgHS9loCEdAsx0lLwnYx3V9lChoBkdAb6LFRYRuj2gHS8RoCEdAsx1t89fTkXV9lChoBkdAcxMw6ySmqGgHS/VoCEdAsx3HmDDjznV9lChoBkdAcWjaCtihFmgHS+NoCEdAsx4ayOaOP3V9lChoBkdAcsJid8RcvGgHS+1oCEdAsx5zNHH3lHV9lChoBkdAcOmSLIgeR2gHS/toCEdAsx7LXxvvSnV9lChoBkdAb69UUfxMFmgHS8FoCEdAsx8Qt5D7ZXV9lChoBkdAcRTUzKs+3mgHS9BoCEdAsx9bfFaStHV9lChoBkdAcKegXuVopWgHS9doCEdAsx+oFOfukXV9lChoBkdAcmkUSZjQRmgHS89oCEdAsx/0ygwoLHV9lChoBkdAcX29lEqlQGgHS/toCEdAsyHJTDO1OXV9lChoBkdAc+24ZdfLLmgHS91oCEdAsyIcDSw4bXV9lChoBkdAcMFoVVPva2gHS9NoCEdAsyJow5/9YXV9lChoBkdAcUZGnn+yaGgHS+JoCEdAsyK+txMnJHV9lChoBkdAbpQdilSCOGgHS9toCEdAsyMQCaJAMXV9lChoBkdAZP34yGi5/mgHTegDaAhHQLMmqFjurp91fZQoaAZHQHDsYESuhbpoB0vPaAhHQLMm+2kSElF1fZQoaAZHQG9WU3wTdtVoB0viaAhHQLMnT7u2JBR1fZQoaAZHQHIwrwOOKfpoB0vtaAhHQLMnqz0HyEt1fZQoaAZHQHBoCgoPTXtoB0vMaAhHQLMn+C/oJRh1fZQoaAZHQHHXy7PIGQloB0vcaAhHQLMoRzQNTcZ1fZQoaAZHQHGkKRQrMC9oB0v0aAhHQLMooW8RL9N1fZQoaAZHQGab3tjTa0xoB03oA2gIR0CzK3nNPgvUdX2UKGgGR0BzUN1+y7f6aAdL6GgIR0CzK83QMQVcdX2UKGgGR0BxNcao/A0saAdL3mgIR0CzLBxe5WildX2UKGgGR0BzgVaouPFOaAdNAAFoCEdAsyx1uTA31nV9lChoBkdAb8m/0ulGgGgHS/hoCEdAsyzPgJkXlHV9lChoBkdAZN7tAs052mgHTegDaAhHQLMvuPXkHUt1fZQoaAZHQHLnT6BRQ79oB0v8aAhHQLMwFy+6Ae91fZQoaAZHQG/sz544ZMtoB0vgaAhHQLMweWYWtU51fZQoaAZHQEWOnWJ79htoB0vBaAhHQLMw18lXzUZ1fZQoaAZHQHIzZbhWHUNoB0viaAhHQLMxP0jTrmh1fZQoaAZHQHJexTsIE8toB0vzaAhHQLMxujMV1wJ1fZQoaAZHQHE8vH1e0HBoB0vdaAhHQLMyNR7JGON1fZQoaAZHQG7e2YWtU4toB0vOaAhHQLMymH0K7Zp1fZQoaAZHQGNo+bNKRMhoB03oA2gIR0CzNXmYF7ladX2UKGgGR0A+rZuyeI2waAdLp2gIR0CzNbY1gpjMdX2UKGgGR0Bxv6CL/CIlaAdLy2gIR0CzNf+vpyIYdX2UKGgGR0ByrJKAavRraAdL7GgIR0CzNlR/NJOGdX2UKGgGR0By3CjpLVWkaAdL8GgIR0CzNqrcbiqAdX2UKGgGR0BoJRi/fwZwaAdN6ANoCEdAszmZuUD+znV9lChoBkdAcihrdFfAsWgHS9loCEdAsznnJp35e3V9lChoBkdAaFAWrwOOKmgHTegDaAhHQLM7U/I8yN51fZQoaAZHQHFvGfXf645oB0vkaAhHQLM7paDf3vh1fZQoaAZHQESJPgvUSZloB0vCaAhHQLM9sWuoxYd1fZQoaAZHQHF+EulGgBdoB0vtaAhHQLM+KjQRf4R1fZQoaAZHQHHLxC+lCTloB0vGaAhHQLM+jY6XBxh1fZQoaAZHQGYsj2rXDm9oB03oA2gIR0CzQC3gk1MudX2UKGgGR0BzoFIH1OCYaAdL+WgIR0CzQIrHMlkZdX2UKGgGR0BMtXQla8pTaAdLqmgIR0CzQMhOk+HKdX2UKGgGR0B0P7TspoboaAdNEwFoCEdAs0KnlaKUFHV9lChoBkdAb1zibUgB92gHS+1oCEdAs0L9+QU5/HV9lChoBkdAcY2Eq2Bre2gHS+FoCEdAs0NRzmwJPnV9lChoBkdAcaxpcophF2gHS75oCEdAs0ObposZpHV9lChoBkdAbWPSE12q1mgHS+BoCEdAs0Ps4cWCVnV9lChoBkdAcRopmmLtNWgHTQUBaAhHQLNES1F6Rhd1fZQoaAZHQHEaFQ2uPmxoB0v1aAhHQLNEp3qAz551fZQoaAZHQHBZpwS8J2NoB0vjaAhHQLNE+h73PAx1fZQoaAZHQGLZuPNmlIpoB03oA2gIR0CzR+fWQOnVdX2UKGgGR0BvibpNbkfcaAdLwGgIR0CzSC3r+o9+dX2UKGgGR0BxoAUBXCCSaAdNWwFoCEdAs0iveWOZLXV9lChoBkdAcTpN2TxG2GgHS/FoCEdAs0kHSMLncXV9lChoBkdAcShOavzOHGgHS9hoCEdAs0lzOY6XB3V9lChoBkdAcXfiUPhAGGgHS+FoCEdAs0niq94/vHV9lChoBkdAckMsI3R5T2gHS8xoCEdAs0w36hxo7HV9lChoBkdAcsQEORT0hGgHS91oCEdAs0yIC8vmHXV9lChoBkdAcczBjFyaNWgHS+FoCEdAs0zbQLNOd3V9lChoBkdAcwJFTvRZ2mgHS/VoCEdAs004f3evZHV9lChoBkdAYzHFKCg9NmgHTegDaAhHQLNOrhsqJ/J1ZS4="
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 5870,
+    "_n_updates": 6360,
     "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 sha256:1803fce78607d9d3bb0636a0ddd4031df66ab6bae0b563b76c62d96348ab4192
+oid sha256:55d627aab12e98b1333e1e63420bf5a4cb78050b5cf6e840ec68c8ce275f3e3a
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b968f98d6f917d2c15195a728c2804c496cba0f1989c89eebb947ed8bf5ba017
+oid sha256:fa709d04a0eb675edc1180e1ba8a69ab46569ff142a3fadc20b5889cb426d8a8
 size 43762

results.json

@@ -1 +1 @@
-{"mean_reward": 266.12007450000004, "std_reward": 36.06393356789779, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-07-14T13:49:07.674475"}
+{"mean_reward": 276.7843308, "std_reward": 23.019425247970013, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-07-14T13:54:55.632640"}