drive that shit better

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 0x7b2f1d90b760>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b2f1d90b7f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b2f1d90b880>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b2f1d90b910>", "_build": "<function ActorCriticPolicy._build at 0x7b2f1d90b9a0>", "forward": "<function ActorCriticPolicy.forward at 0x7b2f1d90ba30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b2f1d90bac0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b2f1d90bb50>", "_predict": "<function ActorCriticPolicy._predict at 0x7b2f1d90bbe0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b2f1d90bc70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b2f1d90bd00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b2f1d90bd90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b2f24253a00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 131072, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1694988610750501190, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAANtg8L5TW0S5LPkDv10HaDzILKC+wBmVu9sIA7/mubU7bzAOv2hKX7p2qr++myptPBmh4b6t/1e8NL3qvtOGDLzs9uC+LsZKPHR84r5x0ve7Xb8bv96TwDshFCa/WBU7PEidv768dtk81bgev8tE5DeSTxC/xvA6vDKAK79+EvS6lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="}, "_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": -0.3107200000000001, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWV4AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHwGkAAAAAAACMAWyUS8iMAXSUR0BXwfnr6ciGdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BXwfCyhSLqdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BXwepjtoi+dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BXweFcpsoEdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3LzK9wm3dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3LI1cdHUdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3JtaY/mldX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3JHqeK8+dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3GRRuTA4dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3Fn27FsIdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3FDF6zE8dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3EV8CxNZdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3DKT0QK8dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3CZOSGJvdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3BuTA31jdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3A1m8M/hdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX3AXVLBbfdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX2/yLAHmjdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX2/YJ3PiUdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX2+0CzTnadX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9yYw7DEWdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9xuTA31jdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9wSvkiljdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9vra/RE4dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9s052hZhdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9sLjPv8ZdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9rn5i3G5dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9q6asp5NdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9puyeI2wdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9o+KTB69dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9oTXarWAdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9navicXndX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9m8Zk079dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9mXPZ7HAdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9l9ORDCxdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BX9lZLZi/gdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEjCpFTegdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEiYG+sYEdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEg9mpVCHdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEgWac7QtdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEdhRZU1idX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEc4HX2/SdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEcTi83+/dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEbmZE2HddX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEaa5PM0QdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEZqEeyRkdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEY/Vy3kQdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEYG+sYEXdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEXo5ggHNdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEXFkxyn2dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEWtITXardX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYEWJN0vGqdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLb+YMOPOdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLbTQVsUJdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLZ39rGipdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLZQ+EAYIdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLWcWj45+dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLVzMibDudX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLVO0svqUdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLUhaC+URdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLTVx0dR0dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLSksSTQmdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLR5xBE8adX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLRBJI1+BdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLQkLQXyidX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLP/NqxkedX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLPlZHNHIdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYLPBi1AqvdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYSG07bL2YdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYSGK64Ds/dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYSEvoNd7fdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYSEIomXw9dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYSBSUC7sfdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYSApKBd2QdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYSAFotcv/dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYR/YjB2wFdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYR+NHYpUhdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYR9deIEbHdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYR8yi22G7dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYR756+nIidX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYR7blA/s3dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYR62a2F37dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYR6cZtNzsdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYR54W1twadX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYpnDiwSrdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYo8EFGG3dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYnhGYrrgdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYm6TW5H3dX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYkETxoZidX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYjbah6BzdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYi4OMERrdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYiLZSNwSdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYhAOavzOdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYgZTAFgVdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYfyPMjeLdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYe67NB4VdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYedkJ8fFdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYd5MURFrdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYdf5ULlWdX2UKGgGR8BpAAAAAAAAaAdLyGgIR0BYYc8kleF+dWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 40, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True]", "bounded_above": "[ True  True]", "_shape": [2], "low": "[-1.2  -0.07]", "high": "[0.6  0.07]", "low_repr": "[-1.2  -0.07]", "high_repr": "[0.6  0.07]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIAwAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "3", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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-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": "1.23.5", "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 0x7b2f1d90b760>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b2f1d90b7f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b2f1d90b880>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b2f1d90b910>", "_build": "<function ActorCriticPolicy._build at 0x7b2f1d90b9a0>", "forward": "<function ActorCriticPolicy.forward at 0x7b2f1d90ba30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b2f1d90bac0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b2f1d90bb50>", "_predict": "<function ActorCriticPolicy._predict at 0x7b2f1d90bbe0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b2f1d90bc70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b2f1d90bd00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b2f1d90bd90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b2f24253a00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1694988898307458575, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAANJF/b7Vie27JHklv2KMyzuhJxm/VCBSO4cKw75TpkE8QzATv0ozLLyoGwe/MFYiuobf1b6Z8467nSIMvxxt9rvnJgq/2Q0HvEHnDL+r1oa7UcIVv1OXqrsW4fS+LsVWvIQt4b5xdkE8G9/9vqTFkjuP+gK//gAROsJCyb7KqLw7lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="}, "_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]", "bounded_above": "[ True  True]", "_shape": [2], "low": "[-1.2  -0.07]", "high": "[0.6  0.07]", "low_repr": "[-1.2  -0.07]", "high_repr": "[0.6  0.07]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIAwAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "3", "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-5.15.109+-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": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

mountain-car-v0.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:700ccc9ca38893a95d8ee94e64cd35594f36ad19fc45da64b72723793e35351d
-size 135464
+oid sha256:35db79702e6a73e8f3294ff8cec4bd60eb960730d4cbcc2a886bd237851e3dd5
+size 135470

mountain-car-v0/data

@@ -21,17 +21,17 @@
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 131072,
-    "_total_timesteps": 100000,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1694988610750501190,
+    "start_time": 1694988898307458575,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAANtg8L5TW0S5LPkDv10HaDzILKC+wBmVu9sIA7/mubU7bzAOv2hKX7p2qr++myptPBmh4b6t/1e8NL3qvtOGDLzs9uC+LsZKPHR84r5x0ve7Xb8bv96TwDshFCa/WBU7PEidv768dtk81bgev8tE5DeSTxC/xvA6vDKAK79+EvS6lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAANJF/b7Vie27JHklv2KMyzuhJxm/VCBSO4cKw75TpkE8QzATv0ozLLyoGwe/MFYiuobf1b6Z8467nSIMvxxt9rvnJgq/2Q0HvEHnDL+r1oa7UcIVv1OXqrsW4fS+LsVWvIQt4b5xdkE8G9/9vqTFkjuP+gK//gAROsJCyb7KqLw7lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -41,17 +41,17 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.3107200000000001,
+    "_current_progress_remaining": -0.015808000000000044,
     "_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": 40,
+    "_n_updates": 248,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",
@@ -77,14 +77,14 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "n_steps": 2048,
-    "gamma": 0.99,
-    "gae_lambda": 0.95,
-    "ent_coef": 0.0,
+    "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": 10,
+    "n_epochs": 4,
     "clip_range": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"

mountain-car-v0/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6ad8df02930d55e842d3a9cf3240b14d2c6fce87f183554046a87fa8dad90a12
+oid sha256:32c07cb89d1cb793204a4f67e8176807e673c6bccdee97bc6d06969bf1a427ce
 size 81273

mountain-car-v0/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0732b0188cd955dc03c350d410e122cdc92b09eed48e20093ff5800c2f37bb02
+oid sha256:e161bae4023ac259e3db6688e845672c980625312e1fa60556afbd2543484100
 size 40001

results.json

@@ -1 +1 @@
-{"mean_reward": -200.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-09-17T22:13:01.224197"}
+{"mean_reward": -200.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-09-17T22:23:05.467331"}