Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 236.34 +/- 45.92
+      value: 278.00 +/- 12.41
       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 0x7fbbf903ef80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbbf903f010>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbbf903f0a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbbf903f130>", "_build": "<function ActorCriticPolicy._build at 0x7fbbf903f1c0>", "forward": "<function ActorCriticPolicy.forward at 0x7fbbf903f250>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fbbf903f2e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbbf903f370>", "_predict": "<function ActorCriticPolicy._predict at 0x7fbbf903f400>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbbf903f490>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbbf903f520>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbbf903f5b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fbbf903a600>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688697420970688278, "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:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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:": "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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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "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 0x7e07b49256c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e07b4925750>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e07b49257e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e07b4925870>", "_build": "<function ActorCriticPolicy._build at 0x7e07b4925900>", "forward": "<function ActorCriticPolicy.forward at 0x7e07b4925990>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e07b4925a20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e07b4925ab0>", "_predict": "<function ActorCriticPolicy._predict at 0x7e07b4925b40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e07b4925bd0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e07b4925c60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e07b4925cf0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e07b4928c40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2015232, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1691462401771794622, "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": -0.007616000000000067, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWV+QsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQE7ICnxaxHKMAWyUS7CMAXSUR0CgNoV9F4LUdX2UKGgGR0BzhIWP91loaAdL4WgIR0CgNo6jN6gNdX2UKGgGR0BuK37iyY5UaAdL3mgIR0CgNttf5ULldX2UKGgGR0Bu0G6shgVoaAdNHgFoCEdAoDbekcjqwHV9lChoBkdAcXdOiFj/dmgHS+doCEdAoDb1KNAC4nV9lChoBkdAcc21cdHUdGgHS+xoCEdAoDeYCW/rSnV9lChoBkdAcIlWo3rD62gHS/BoCEdAoDhMq6OHWXV9lChoBkdAcZdQJXyRS2gHS9hoCEdAoDj3D1oQF3V9lChoBkdAbwlP6be/H2gHS/hoCEdAoDmA8U21lXV9lChoBkdAcQ4hF3IMjWgHS/poCEdAoDmUuYhManV9lChoBkdAcnGCcPOIImgHS8hoCEdAoDnysjmjkHV9lChoBkdAc5jR7JGOMmgHS9doCEdAoDn3Ye1a4nV9lChoBkdAcSiufVZs9GgHS+loCEdAoDplSQ5my3V9lChoBkdAclrp/PPcBWgHS+hoCEdAoDqDgn+hoXV9lChoBkdAc5gwcHWz4WgHS+toCEdAoDr3Olfqo3V9lChoBkdAcIOr433pOmgHS/JoCEdAoDsUWXTmXHV9lChoBkdAchaoTPBzm2gHTXwBaAhHQKA7IMBp5/t1fZQoaAZHQHNi/K+zt1JoB0v2aAhHQKA7QTJyQxN1fZQoaAZHQHKr6cRUWEdoB0vhaAhHQKA7l20Re1N1fZQoaAZHQG+DyJ9AoodoB0vraAhHQKA8YAYHgP51fZQoaAZHQHB3pL7GecxoB0viaAhHQKA80Kb8WKx1fZQoaAZHQHLKanaWX1JoB00fAmgIR0CgPQRiw0O3dX2UKGgGR0BxcVmpVCHAaAdL2WgIR0CgPS4axX4kdX2UKGgGR0BxXtas6q82aAdL0GgIR0CgPVhYNiH7dX2UKGgGR0BwQaCK77KraAdL0mgIR0CgPV7o0Q9SdX2UKGgGR0BxI4HhS9/SaAdLxGgIR0CgPYP5YYBOdX2UKGgGR0Bx/loSL61taAdNCQFoCEdAoD3Vw71ZknV9lChoBkdAcbrmmtQsPWgHS9ZoCEdAoD3bvNNahnV9lChoBkdAcrQCp3os7WgHS9poCEdAoD5NENOM2nV9lChoBkdAcSBHKwIMSmgHTXwDaAhHQKA+mz3yqdZ1fZQoaAZHQHMR4a5wwTNoB00BAWgIR0CgPv2MS9M9dX2UKGgGR0BvpbjxTbWVaAdL/mgIR0CgPvx2KVIJdX2UKGgGR0Bzf3RrrPdEaAdNxQJoCEdAoEiZisny/nV9lChoBkdAcrvtVJcxCmgHTTIBaAhHQKBIuml67d11fZQoaAZHQHCaveP7vXtoB00fAWgIR0CgSMkC3gDSdX2UKGgGR0Byb3vCuU2UaAdL9WgIR0CgSVKS5iEydX2UKGgGR0ByfyRZEDyOaAdL7mgIR0CgSWfHYHxCdX2UKGgGR0BxBCbWmP5paAdL/WgIR0CgScse4kNXdX2UKGgGR0ByKMFxGUfQaAdL9mgIR0CgSdmUfPondX2UKGgGR0BzQX4ubqhUaAdL2GgIR0CgSe+J53TvdX2UKGgGR0ByFhs7+1jRaAdNGwFoCEdAoEqleQdS23V9lChoBkdAcVIGfwqiGmgHTToBaAhHQKBLA50bLlp1fZQoaAZHQHHt4bsF+uxoB0vSaAhHQKBLFrN4Z/F1fZQoaAZHQHDNAZbY9PloB00hAWgIR0CgSyDriVB2dX2UKGgGR0BteWI2wV0taAdL22gIR0CgSzjNQj2SdX2UKGgGR0BxWJqWTot+aAdNCwFoCEdAoEtB6hQFcXV9lChoBkdAcnnp1ie/YmgHTSEBaAhHQKBL0tfXwsp1fZQoaAZHQHOeoxpL26FoB0vUaAhHQKBL/bKzRhN1fZQoaAZHQG7syd4FA3VoB0vZaAhHQKBMAlchTwV1fZQoaAZHQHGs+Zb6guhoB0viaAhHQKBMBfcer+51fZQoaAZHQHHcl2icoYxoB0vMaAhHQKBM1ngYP5J1fZQoaAZHQHCKiS3b215oB0vqaAhHQKBM1L2YfGN1fZQoaAZHQHN7XMUypJhoB0vmaAhHQKBM2wL3K0V1fZQoaAZHQG70y4vvjOtoB0vTaAhHQKBM+ZNO/L11fZQoaAZHQFEBouf29L9oB0uYaAhHQKBNHE61b7l1fZQoaAZHQHAKYcinpB5oB0v2aAhHQKBNg/h2nsN1fZQoaAZHQG/LbFsHjZNoB0vUaAhHQKBODLlFMIx1fZQoaAZHQHOmrCBPKuBoB0vXaAhHQKBOMh9LHuJ1fZQoaAZHQHG/W5MDfWNoB01pAmgIR0CgTmACOmzjdX2UKGgGR0BxOhlMAWBSaAdNDQFoCEdAoE56qOtGNXV9lChoBkdAcl457PY4AGgHS/hoCEdAoE62Lm6oVHV9lChoBkdAcdIx/d69kGgHS9BoCEdAoE6+za9K3HV9lChoBkdAcdYPOpsGgWgHS9xoCEdAoE8PEhq0t3V9lChoBkdAcsZccENe+mgHS+toCEdAoE9Lqv/za3V9lChoBkdAcOhGM4tHx2gHTTUBaAhHQKBPYLWqcVh1fZQoaAZHQHImSBXjlxRoB00OAWgIR0CgT8FHJ9y+dX2UKGgGR0Byx8NKAavSaAdL1WgIR0CgT8mwA2hqdX2UKGgGR0Bzqmby6MBIaAdL1GgIR0CgUArt3OfNdX2UKGgGR0BzRUy/KyOaaAdL7GgIR0CgUBNLUTcqdX2UKGgGR0Byi+N6w+t9aAdL6mgIR0CgUDCjL0SRdX2UKGgGR0BySBEYwZflaAdNBAFoCEdAoFBnr8iwCHV9lChoBkdAcK1KBNEgGWgHS9hoCEdAoFB56Skj5nV9lChoBkdAb0PmnwXqJWgHS95oCEdAoFEHYHxBmnV9lChoBkdAcwhV8Ti84GgHS+xoCEdAoFFddAxBV3V9lChoBkdAcrOnuRcNY2gHS/NoCEdAoFGhwwTM7nV9lChoBkdAcZy07KaG6GgHS89oCEdAoFIccp9ZzXV9lChoBkdAclZPuG9HtmgHTQwBaAhHQKBSIbQTmGN1fZQoaAZHQHMEC79Q40doB0v+aAhHQKBSLd7fHgh1fZQoaAZHQHIcFOj7AL1oB00BAWgIR0CgUkH4XXRPdX2UKGgGR0Bxt9o6CDmKaAdLwmgIR0CgUm7NKRMfdX2UKGgGR0BxCwVN5+pgaAdL92gIR0CgUnaQ/5ckdX2UKGgGR0BxYUAQxvehaAdL42gIR0CgUuT8P4EfdX2UKGgGR0ByF8wvg3tKaAdNAgFoCEdAoFLl9v0h/3V9lChoBkdAbj5RR/EwWWgHS9hoCEdAoFMIyylennV9lChoBkdAcRPGYKIBR2gHS+RoCEdAoFMmZJCjUXV9lChoBkdAcocVbzK9wmgHTQEBaAhHQKBTpypaRp11fZQoaAZHQHK384T9KmNoB0vyaAhHQKBTwfHxSYR1fZQoaAZHQHNFtWU8mrtoB0v+aAhHQKBT1kbxVhl1fZQoaAZHQHM2PGp++dtoB0vuaAhHQKBURp6hQFd1fZQoaAZHQG7r3Q2MsH1oB0veaAhHQKBUYcAiml91fZQoaAZHQHJEMifQKKJoB0vQaAhHQKBUcqvNeMR1fZQoaAZHQHGSMPnSv1VoB0u9aAhHQKBUnkCmuT11fZQoaAZHQHO/i75Ec81oB0vMaAhHQKBU1n27FsJ1fZQoaAZHQHLjvEOy3TdoB0vVaAhHQKBVBOymhuh1fZQoaAZHQHDog6U7jkxoB0vRaAhHQKBVHtx+8Xh1fZQoaAZHQHIrt7fHggpoB00KAWgIR0CgVZkd3jdYdX2UKGgGR0BuXhYaHbh4aAdL0mgIR0CgVeSCFsYVdX2UKGgGR0BxuojzI3iraAdNDAFoCEdAoFXxs67ulXV9lChoBkdAcIif0VafSWgHS+ZoCEdAoFYJ3NcGDHV9lChoBkdAciY2JSBK+WgHS/1oCEdAoFYzk6tDD3VlLg=="}, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "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:f521704c3e5a1fb2f09b06150902f58d500eb2acd9a6fd72d4c1d477e2dae17b
-size 146735
+oid sha256:06baac8de865a36f88c2e5e48bbfcc1fdb55cc6febd613462aeda6c084a80261
+size 146658

ppo-LunarLander-v2/data

@@ -4,34 +4,34 @@
         ":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 0x7fbbf903ef80>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbbf903f010>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbbf903f0a0>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbbf903f130>",
-        "_build": "<function ActorCriticPolicy._build at 0x7fbbf903f1c0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7fbbf903f250>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fbbf903f2e0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbbf903f370>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7fbbf903f400>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbbf903f490>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbbf903f520>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbbf903f5b0>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7e07b49256c0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e07b4925750>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e07b49257e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e07b4925870>",
+        "_build": "<function ActorCriticPolicy._build at 0x7e07b4925900>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7e07b4925990>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e07b4925a20>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e07b4925ab0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7e07b4925b40>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e07b4925bd0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e07b4925c60>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e07b4925cf0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7fbbf903a600>"
+        "_abc_impl": "<_abc._abc_data object at 0x7e07b4928c40>"
     },
     "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": 1688697420970688278,
+    "start_time": 1691462401771794622,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAHq8Fj5RC3g+nT0PvgtwLL4rcVS9GPEovAAAAAAAAAAA02kPPvRdk7zbkb48MsBqvhpFXLwmXny+AACAPwAAgD/mYFk9UvW3uxVkazqMx1k8kuQfPZ1nO70AAIA/AACAPyZCmT0pbAi6Ds48s71QNC+5gYC7LinGMwAAgD8AAIA/2gaPPQXpqLtX80Y8hD6hPABT+jwMToi9AACAPwAAgD9amN69zWDZPjcbHTttREm+YDkAvV3TjL0AAAAAAAAAAJqjszwppGa68N3/M6nuNy3203M7wQaqswAAgD8AAIA/M0qKPY/nJbzyJRk86TcZPbspjj3FgPa9AACAPwAAgD/Gaki+j3sJPwrwZD4JgKC+dE1FvAohpD0AAAAAAAAAANMsO75Zp3o/CNEpvrQlur7AGzK+ZnQiPQAAAAAAAAAADevCPVzbJLo6jCE141AyMIaMUjsT/lS0AAAAAAAAgD9muJ69JcdJPj4lPL2HX4C+r2myvb+DKD0AAAAAAAAAAACIIz1Pcxm8VMABPP8Oqzwn4YC9KuWMPQAAgD8AAIA/gAVRvRRMhbovO7075LCIOJ/IzTpuLa63AACAPwAAgD9mr8S8rnWVum7IO7PQPvWurBuPule9wDMAAIA/AACAPxq8Ab2ZPBg/IVcovV2Zgr6YNG+9YzlWOgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -41,17 +41,17 @@
     "_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": 248,
+    "_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 sha256:5d27fb1e08fb153f1f71cabb180c33b518e4942db298d741ecbb4e0438a05d95
+oid sha256:c56875562d0260536aa686a412d6b919b77d081b32656a2c30deb93748d7c671
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:63b549b1c983d7125cc2f375b423d9c8d057ea2476dc295f54b71f39554a4139
+oid sha256:4d387bcb7414c3221d2c37b68e01553c2b6414743a0f980d3e8cd37d98e589dd
 size 43329

ppo-LunarLander-v2/system_info.txt

@@ -1,4 +1,4 @@
-- OS: Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
+- OS: Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
 - Python: 3.10.12
 - Stable-Baselines3: 2.0.0a5
 - PyTorch: 2.0.1+cu118

results.json

@@ -1 +1 @@
-{"mean_reward": 236.34390833966148, "std_reward": 45.92433272621777, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-07T03:06:49.264334"}
+{"mean_reward": 277.99602619582515, "std_reward": 12.408313526211737, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-08-08T03:22:40.226682"}