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sac-MountainCarContinuous-v0-1430860601

Reinforcement Learning
stable-baselines3
MountainCarContinuous-v0
deep-reinforcement-learning
Eval Results
Model card Files Community
sac-MountainCarContinuous-v0-1430860601
File size: 17,874 Bytes 
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{
    "policy_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnNhYy5wb2xpY2llc5SMCVNBQ1BvbGljeZSTlC4=",
        "__module__": "stable_baselines3.sac.policies",
        "__doc__": "\n    Policy class (with both actor and critic) for SAC.\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 use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` when using gSDE 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 clip_mean: Clip the mean output when using gSDE to avoid numerical instability.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    :param n_critics: Number of critic networks to create.\n    :param share_features_extractor: Whether to share or not the features extractor\n        between the actor and the critic (this saves computation time)\n    ",
        "__init__": "<function SACPolicy.__init__ at 0x7fdc5fd92ca0>",
        "_build": "<function SACPolicy._build at 0x7fdc5fd92d30>",
        "_get_constructor_parameters": "<function SACPolicy._get_constructor_parameters at 0x7fdc5fd92dc0>",
        "reset_noise": "<function SACPolicy.reset_noise at 0x7fdc5fd92e50>",
        "make_actor": "<function SACPolicy.make_actor at 0x7fdc5fd92ee0>",
        "make_critic": "<function SACPolicy.make_critic at 0x7fdc5fd92f70>",
        "forward": "<function SACPolicy.forward at 0x7fdc5fd9a040>",
        "_predict": "<function SACPolicy._predict at 0x7fdc5fd9a0d0>",
        "set_training_mode": "<function SACPolicy.set_training_mode at 0x7fdc5fd9a160>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7fdc603cdfc0>"
    },
    "verbose": 1,
    "policy_kwargs": {
        "log_std_init": -3.67,
        "net_arch": [
            64,
            64
        ],
        "use_sde": true
    },
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
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        "dtype": "float32",
        "_shape": [
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        ],
        "low": "[-1.2  -0.07]",
        "high": "[0.6  0.07]",
        "bounded_below": "[ True  True]",
        "bounded_above": "[ True  True]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
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        "dtype": "float32",
        "_shape": [
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        ],
        "low": "[-1.]",
        "high": "[1.]",
        "bounded_below": "[ True]",
        "bounded_above": "[ True]",
        "_np_random": "RandomState(MT19937)"
    },
    "n_envs": 1,
    "num_timesteps": 50016,
    "_total_timesteps": 50000,
    "_num_timesteps_at_start": 0,
    "seed": 0,
    "action_noise": null,
    "start_time": 1671733073573371710,
    "learning_rate": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
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    "tensorboard_log": null,
    "lr_schedule": {
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    },
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    "_last_episode_starts": {
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    "_last_original_obs": {
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    "_episode_num": 431,
    "use_sde": true,
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    "batch_norm_stats_target": []
}