Upload PPO LunarLander-v2 trained agent v2 2M

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 210.73 +/- 77.64
+      value: 273.93 +/- 26.88
       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 0x7c79ad44d000>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c79ad44d090>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c79ad44d120>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c79ad44d1b0>", "_build": "<function ActorCriticPolicy._build at 0x7c79ad44d240>", "forward": "<function ActorCriticPolicy.forward at 0x7c79ad44d2d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c79ad44d360>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c79ad44d3f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c79ad44d480>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c79ad44d510>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c79ad44d5a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c79ad44d630>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c79bae09d40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1725814826201483370, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVQgwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGdzHE2pAD+MAWyUTegDjAF0lEdAlyQqSX+l03V9lChoBkdAYwLkmQbMo2gHTegDaAhHQJcmaM3qAz51fZQoaAZHQGPxMNlRP45oB03oA2gIR0CXKxLcKw6idX2UKGgGR0BdaSxNZeRgaAdN6ANoCEdAly1dv863iXV9lChoBkdAZeFTG5tm+WgHTegDaAhHQJctkYj0L+h1fZQoaAZHQGJ2cIzFdcBoB03oA2gIR0CXLz8cdYGMdX2UKGgGR0BmmelImPYGaAdN6ANoCEdAlzDSOmzjWHV9lChoBkdAZnjM0P6KtWgHTegDaAhHQJc+9GkN4JN1fZQoaAZHQGOzs0YTCchoB03oA2gIR0CXQ10A93bFdX2UKGgGR0BjsBdD6WPcaAdN6ANoCEdAl0foT0xubnV9lChoBkdAbeYb7TDwY2gHTbYBaAhHQJdfYRJ2+wl1fZQoaAZHQGV4sir1dxBoB03oA2gIR0CXYJA+pwS8dX2UKGgGR0Bi1mOS4e90aAdN6ANoCEdAl2LvFWGRFXV9lChoBkdAY89TkyULUmgHTegDaAhHQJdkBCfHxSZ1fZQoaAZHQGXCVB+nZTRoB03oA2gIR0CXaP8w5/9YdX2UKGgGR0BhmWCoS+QEaAdN6ANoCEdAl2laCcwxnHV9lChoBkdAYS0neBQN1GgHTegDaAhHQJdq8N6PbPB1fZQoaAZHQHEFko8ZDRdoB01tAWgIR0CXbdWLgn+idX2UKGgGR0Bkj3PcBU70aAdN6ANoCEdAl3UO23KB/nV9lChoBkdAYPwRYA80UGgHTegDaAhHQJd3Lv1DjR51fZQoaAZHQGKkj2rXDm9oB03oA2gIR0CXe3L1EmY0dX2UKGgGR0Bi3gffXPJJaAdN6ANoCEdAl32i2UjcEnV9lChoBkdAXakplSS/02gHTegDaAhHQJd908Swnpl1fZQoaAZHQF6VZ7XxvvVoB03oA2gIR0CXgHyquKXOdX2UKGgGR0BmDqij+JgtaAdN6ANoCEdAl4vslC1JDnV9lChoBkdAbGMy4Wk8BGgHTdECaAhHQJeSZekYXO51fZQoaAZHQGMIqEeyRjloB03oA2gIR0CXlG24uscRdX2UKGgGR0BkUvNZ/0/XaAdN6ANoCEdAl5ks4ku6E3V9lChoBkdAZFmUr08NhGgHTegDaAhHQJetkyCWeH11fZQoaAZHQGBhEIgNgBtoB03oA2gIR0CXr4G2TgVHdX2UKGgGR0Blvk+iaiK0aAdN6ANoCEdAl7BCrPt2LnV9lChoBkdAYwcf029+PWgHTegDaAhHQJezrsRg7YF1fZQoaAZHQGRX5U1hsqJoB03oA2gIR0CXs+x6fJ3gdX2UKGgGR0Bi31GiHqNZaAdN6ANoCEdAl7dkHdGiH3V9lChoBkdAX3gzi0fHP2gHTegDaAhHQJe/BFLFn7J1fZQoaAZHQGRpRekYXO5oB03oA2gIR0CXwSv1UVBVdX2UKGgGR0BhckMuvlltaAdN6ANoCEdAl8XM1jy4F3V9lChoBkdAXnVOgxrSE2gHTegDaAhHQJfIHjFQ2uR1fZQoaAZHQFwQLUkOZstoB03oA2gIR0CXyEv9LpRodX2UKGgGR0BhpshxHXmOaAdN6ANoCEdAl8vbBsQ/YHV9lChoBkdAYaseXAuZkWgHTegDaAhHQJfakmJFb3Z1fZQoaAZHQGO2uyE+PiloB03oA2gIR0CX4arNnoPkdX2UKGgGR0BjEaV6eGwiaAdN6ANoCEdAl+PcqWkadnV9lChoBkdAbWoOinHeamgHTS0DaAhHQJflbM7lq8F1fZQoaAZHQGRRvFFUhmpoB03oA2gIR0CX59J/oaDPdX2UKGgGR0BnorU1AJLNaAdN6ANoCEdAl+kIUN8VpXV9lChoBkdAYcy5yU9py2gHTegDaAhHQJf8BvYODrZ1fZQoaAZHQG8C0c4o7V9oB00RAmgIR0CX/C+MIeHSdX2UKGgGR0BgVZAdGRV7aAdN6ANoCEdAl/y/kWAPNHV9lChoBkdAY+4sunMt9WgHTegDaAhHQJgBZjXnQpp1fZQoaAZHQGI2PvBrN4ZoB03oA2gIR0CYBkSGJvYOdX2UKGgGR0BmxloexOclaAdN6ANoCEdAmA8eMVDa5HV9lChoBkdAZfLZWaMJhWgHTegDaAhHQJgRd1mrbQF1fZQoaAZHQGcHlWn0kGBoB03oA2gIR0CYFj8K5TZQdX2UKGgGR0BlowdsBQvYaAdN6ANoCEdAmBiHwTdtVXV9lChoBkdAYGmW3z+WGGgHTegDaAhHQJgbpVbRne11fZQoaAZHQF/CEJBw++xoB03oA2gIR0CYKRZYgaFVdX2UKGgGR0Bh7TpC8e0YaAdN6ANoCEdAmC97s4T9KnV9lChoBkdAZVeFmFrVOWgHTegDaAhHQJgxzX6InBt1fZQoaAZHQGLbZooNNJxoB03oA2gIR0CYM7wJPZZkdX2UKGgGR0Bi4CGvfTCtaAdN6ANoCEdAmDaLUb1h9nV9lChoBkdAZaxy0a6z3WgHTegDaAhHQJg4CbI91U51fZQoaAZHQGOQRc/t6X1oB03oA2gIR0CYTBBBAv+PdX2UKGgGR0Bi9tlkH2RJaAdN6ANoCEdAmEw3Y6GQCHV9lChoBkdAYr/w3o9s8GgHTegDaAhHQJhMxB3Roh91fZQoaAZHQGKo+f7JnxtoB03oA2gIR0CYUClbeMyadX2UKGgGR0BjOHBpHqeLaAdN6ANoCEdAmFOlocrAg3V9lChoBkdAY5WaZQYUFmgHTegDaAhHQJhb2/XXiBJ1fZQoaAZHQGWtvkq+ajNoB03oA2gIR0CYXiB/qgRLdX2UKGgGR0A3pRNh3JPqaAdNCwFoCEdAmF5ZTqB3A3V9lChoBkdAcQU48lolEGgHTRoCaAhHQJhhMKa5PM11fZQoaAZHQGU4w/gR9PVoB03oA2gIR0CYYl4Y77sOdX2UKGgGR0BlJdJ6IFeOaAdN6ANoCEdAmGRYTGo73nV9lChoBkdAYCdmGucME2gHTegDaAhHQJhn+tyPuG91fZQoaAZHQEG615Sm65JoB0vqaAhHQJhy5qmCROl1fZQoaAZHQGOKiyyD7IloB03oA2gIR0CYdF3zcynDdX2UKGgGR0Bw4rQrtmcwaAdN4wNoCEdAmHnl90A93nV9lChoBkdAVljQC0WuYGgHTegDaAhHQJh9Xo3aSLZ1fZQoaAZHQGL6PL5hz/9oB03oA2gIR0CYf3+fAbhndX2UKGgGR0BjiTMA3kxRaAdN6ANoCEdAmICLvgFX73V9lChoBkdAZH2NhmXgL2gHTegDaAhHQJiCS2MKkVN1fZQoaAZHQGjqmXXyy2RoB03oA2gIR0CYgm8KXv6TdX2UKGgGR0BY+7Y02tMgaAdN6ANoCEdAmILxUFSsKnV9lChoBkdAY2Q0svqTr2gHTegDaAhHQJib6MefZmJ1fZQoaAZHQErXAbhm5DtoB0viaAhHQJigR13dKul1fZQoaAZHQDA1fw7T2FpoB00oAWgIR0CYpP/ZuhsZdX2UKGgGR0BhuJt1p0wKaAdN6ANoCEdAmKU4lQdjonV9lChoBkdAZKRDLKV6eGgHTegDaAhHQJinVppN9IB1fZQoaAZHQF756jFhodxoB03oA2gIR0CYp4qe9SMtdX2UKGgGR0BgHpje9Ba+aAdN6ANoCEdAmKoeq3mV7nV9lChoBkdAY4+r/bTMJWgHTegDaAhHQJirLX18LKF1fZQoaAZHQGTXk3S8an9oB03oA2gIR0CYr2N1QqI8dX2UKGgGR0A3VgJTl1bJaAdNDwFoCEdAmLROYYzi0nV9lChoBkdAZBLlxwQ18GgHTegDaAhHQJi4mv6j3251fZQoaAZHQGviE8RtgrpoB037AmgIR0CYuad6LOzIdX2UKGgGR0Be+dix3V0+aAdN6ANoCEdAmLnxb4agmXV9lChoBkdAZkImrKeTV2gHTegDaAhHQJi/GPBBRht1fZQoaAZHQGLOW3z+WGBoB03oA2gIR0CYwo4WDYh/dX2UKGgGR0BmJMHQhOgyaAdN6ANoCEdAmMS8C5mRNnV9lChoBkdAXoIZjx0+1WgHTegDaAhHQJjICCbtqpN1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 252, "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": 16, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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": "2.4.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "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 0x7c5b516129e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c5b51612a70>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c5b51612b00>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c5b51612b90>", "_build": "<function ActorCriticPolicy._build at 0x7c5b51612c20>", "forward": "<function ActorCriticPolicy.forward at 0x7c5b51612cb0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c5b51612d40>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c5b51612dd0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c5b51612e60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c5b51612ef0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c5b51612f80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c5b51613010>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c5b515aba00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2015232, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1726317914029663378, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAQAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.007616000000000067, "_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": 492, "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": 16, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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": "2.4.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "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 sha256:384fe2a14590898afbbf6ff01e5ffe2d5e96ff21e2c6283a68a69f9e12d1afe7
-size 148084
+oid sha256:18f6798ed37635ef3e2f256cc108c5420a45a2add3d2d86154a2705e4ad773c9
+size 148000

ppo-LunarLander-v2/data

@@ -4,54 +4,54 @@
         ":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 0x7c79ad44d000>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c79ad44d090>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c79ad44d120>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c79ad44d1b0>",
-        "_build": "<function ActorCriticPolicy._build at 0x7c79ad44d240>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7c79ad44d2d0>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c79ad44d360>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c79ad44d3f0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7c79ad44d480>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c79ad44d510>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c79ad44d5a0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c79ad44d630>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7c5b516129e0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c5b51612a70>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c5b51612b00>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c5b51612b90>",
+        "_build": "<function ActorCriticPolicy._build at 0x7c5b51612c20>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7c5b51612cb0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c5b51612d40>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c5b51612dd0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7c5b51612e60>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c5b51612ef0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c5b51612f80>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c5b51613010>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7c79bae09d40>"
+        "_abc_impl": "<_abc._abc_data object at 0x7c5b515aba00>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 2015232,
+    "_total_timesteps": 2000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1725814826201483370,
+    "start_time": 1726317914029663378,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAQAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
     },
     "_last_original_obs": null,
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.015808000000000044,
+    "_current_progress_remaining": -0.007616000000000067,
     "_stats_window_size": 100,
     "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": 252,
+    "_n_updates": 492,
     "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 sha256:78dc40cdbd4ded05265d9225bfd73b0960b55a9b1c9b5071b191e5b967b2dfa6
+oid sha256:77d6dbbfe0ba05dc27fbc914b1596cf27a44367fd3ec9be91a7e66f1e8e663fb
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ce745f33a938274ffaa4828326e1b4e8b62d6a42d212c3529140b4d9a02b9eb0
+oid sha256:5b406b85b728ef6dda4efa2f3befdd97a96f73ad01e748459bbf5fa1aae05012
 size 43762

results.json

@@ -1 +1 @@
-{"mean_reward": 210.72687331430498, "std_reward": 77.63651954540022, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-09-08T17:24:46.187522"}
+{"mean_reward": 273.92913418361616, "std_reward": 26.879198666904212, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-09-14T13:35:47.215552"}