robotman0's picture
default params for 1 million timesteps
d0f75d7
{
"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 0x7f774605e670>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f774605e700>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f774605e790>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f774605e820>",
"_build": "<function ActorCriticPolicy._build at 0x7f774605e8b0>",
"forward": "<function ActorCriticPolicy.forward at 0x7f774605e940>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f774605e9d0>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f774605ea60>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f774605eaf0>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f774605eb80>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f774605ec10>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f774605f150>"
},
"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": 1670956415107810284,
"learning_rate": 0.0003,
"tensorboard_log": null,
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
},
"_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": 310,
"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
}