Sami's picture
Upload model: PPO-LunarLander-v2, version: 6.000000
0b0401a
{
"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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7fcf5c4725f0>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcf5c472680>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcf5c472710>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcf5c4727a0>",
"_build": "<function ActorCriticPolicy._build at 0x7fcf5c472830>",
"forward": "<function ActorCriticPolicy.forward at 0x7fcf5c4728c0>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcf5c472950>",
"_predict": "<function ActorCriticPolicy._predict at 0x7fcf5c4729e0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcf5c472a70>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcf5c472b00>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcf5c472b90>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7fcf5c4be720>"
},
"verbose": 1,
"policy_kwargs": {},
"observation_space": {
":type:": "<class 'gym.spaces.box.Box'>",
":serialized:": "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",
"dtype": "float32",
"_shape": [
8
],
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
"high": "[inf inf inf inf inf inf inf inf]",
"bounded_below": "[False False False False False False False False]",
"bounded_above": "[False False False False False False False False]",
"_np_random": null
},
"action_space": {
":type:": "<class 'gym.spaces.discrete.Discrete'>",
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
"n": 4,
"_shape": [],
"dtype": "int64",
"_np_random": null
},
"n_envs": 16,
"num_timesteps": 1015808,
"_total_timesteps": 1000000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1651690616.387879,
"learning_rate": 0.0003,
"tensorboard_log": null,
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"_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,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 1272,
"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
}