ppo-LunarLander-v2 / config.json
tegpro's picture
my first model
56f44f3 verified
Raw
History Blame Contribute Delete
13.8 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 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 0x78348a4b0c20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78348a4b0cc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78348a4b0d60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78348a4b0e00>", "_build": "<function ActorCriticPolicy._build at 0x78348a4b0ea0>", "forward": "<function ActorCriticPolicy.forward at 0x78348a4b0f40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78348a4b0fe0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78348a4b1080>", "_predict": "<function ActorCriticPolicy._predict at 0x78348a4b1120>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78348a4b11c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78348a4b1260>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78348a4b1300>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78348a41a8c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1779454022862167485, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAAAtYn0+8W0lvVAFRThsXI232kWOvjVzb7cAAIA/AACAP81hsr1Sov86ItuBPfs+AjulZcm7EvS+uwAAAAAAAAAA5tQIvfGQiz9Wl8m9mnZRv1fmtbvdlNq9AAAAAAAAAAAAmaY9+xO/PbbLyr3sFAy+qDiLvOhMubwAAAAAAAAAAKBdRj4knRo86gQcvhV28r0+VtU9JoocPwAAgD8AAIA/4PM2vi7erLymWH67IALjuWmwFD6sY646AACAPwAAgD9gH2s+fW8Fve6PObuJS9w5BeptvvgAeToAAIA/AACAP2ZrjrxLDEc/k/5uvZwAU7+g/gG9Wv7TvAAAAAAAAAAAPYVivojAJD9A64C+mWsov766f76N7yw9AAAAAAAAAADA1MC9HOclvHK7vz0KfyW94BWDPUoECj4AAIA/AACAP7PoDb7IG68/kvPcviIO8r6P8me9N4kKvQAAAAAAAAAA4LxwPjgGUD8LJdQ+UYsOv0uvyT6jFmE+AAAAAAAAAADmEWs+xGMPvWmrrDv+xz26NBl9vqRSELsAAIA/AACAP1rZhz3gv70/KtOePtzS6r1ycTo9tYZoPQAAAAAAAAAA8tWQvlofbT9urui+RYg8vzGycb5flhK+AAAAAAAAAABmSqo7cU8/u9V6+zzF/g49LOg5vBDP8D0AAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLEEsIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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": 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, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV/gAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoC4wCaTiUiYiHlFKUKEsDaA9OTk5K/////0r/////SwB0lGKMCl9ucF9yYW5kb22UTnViLg==", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.6.122+-x86_64-with-glibc2.35 # 1 SMP Thu Apr 30 18:17:14 UTC 2026", "Python": "3.12.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.10.0+cu128", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.2", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}