ppo-LunarLander-v2 / config.json
mgfrantz's picture
Trained LunarLander-v2-PPO-0 with a reduced learning rate by a factor of 10
a2102ab
raw
history blame
14.3 kB
{"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 0x7fe16a6b8830>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe16a6b88c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe16a6b8950>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe16a6b89e0>", "_build": "<function ActorCriticPolicy._build at 0x7fe16a6b8a70>", "forward": "<function ActorCriticPolicy.forward at 0x7fe16a6b8b00>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe16a6b8b90>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe16a6b8c20>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe16a6b8cb0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe16a6b8d40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe16a6b8dd0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe16a691240>"}, "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": 5013504, "_total_timesteps": 5000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652293825.0681405, "learning_rate": 2.9999999999999997e-06, "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": -0.0027007999999999477, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 10120, "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, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}