Upload PPO LunarLander trained agent

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 265.77 +/- 20.87
+      value: 261.24 +/- 15.44
       name: mean_reward
     task:
       type: reinforcement-learning

config.json

@@ -1 +1 @@
-{"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 0x7f76eae65ef0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f76eae65f80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f76eae6d050>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f76eae6d0e0>", "_build": "<function ActorCriticPolicy._build at 0x7f76eae6d170>", "forward": "<function ActorCriticPolicy.forward at 0x7f76eae6d200>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f76eae6d290>", "_predict": "<function ActorCriticPolicy._predict at 0x7f76eae6d320>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f76eae6d3b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f76eae6d440>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f76eae6d4d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f76eaeb2990>"}, "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": 1651690340.8516178, "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:": "gAWVaRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIE+6Veev6cECUhpRSlIwBbJRNBgGMAXSUR0CZfhHu7YkFdX2UKGgGaAloD0MIkpVfBmP+cECUhpRSlGgVS/hoFkdAmX5tm16VuHV9lChoBmgJaA9DCLwH6L6cr3FAlIaUUpRoFU0WAWgWR0CZfrXizcASdX2UKGgGaAloD0MI4xqfyT5EcUCUhpRSlGgVTRQBaBZHQJl/QNG3F1l1fZQoaAZoCWgPQwhbP/1nze1xQJSGlFKUaBVNAwFoFkdAmX/jqbBoEnV9lChoBmgJaA9DCPqbUIiAK0FAlIaUUpRoFUvJaBZHQJl/3uqm0md1fZQoaAZoCWgPQwiTizGwjudyQJSGlFKUaBVNVQFoFkdAmX/Jz90ihXV9lChoBmgJaA9DCEw2HmwxC3BAlIaUUpRoFU0WAWgWR0CZgfGkep4sdX2UKGgGaAloD0MI0m9fB04Mc0CUhpRSlGgVS9loFkdAmYH/O+qR2nV9lChoBmgJaA9DCGzRArStk3BAlIaUUpRoFU0OAWgWR0CZglc1O0swdX2UKGgGaAloD0MI1H5rJ0q9cUCUhpRSlGgVTRYBaBZHQJmCuI1tO211fZQoaAZoCWgPQwjoMcozr+xyQJSGlFKUaBVNCgFoFkdAmYMeV5a/y3V9lChoBmgJaA9DCLQc6KE2+mtAlIaUUpRoFU0MAWgWR0CZg2SmZVn3dX2UKGgGaAloD0MIJsgIqLBFcECUhpRSlGgVTTQBaBZHQJmDw3o9s8B1fZQoaAZoCWgPQwhN1qiH6M5wQJSGlFKUaBVNLQFoFkdAmYQNY8uBc3V9lChoBmgJaA9DCDY9KCiFenBAlIaUUpRoFUv4aBZHQJmENzvJA+p1fZQoaAZoCWgPQwgLDi+IyAVwQJSGlFKUaBVL8mgWR0CZhInUDuBudX2UKGgGaAloD0MIfCk8aHbXcECUhpRSlGgVTQYBaBZHQJmFmuA7Ppp1fZQoaAZoCWgPQwjilLn5RrlwQJSGlFKUaBVNHQFoFkdAmYXzGxUvPHV9lChoBmgJaA9DCKIL6lumanFAlIaUUpRoFUvtaBZHQJmGIbp/wy91fZQoaAZoCWgPQwgM5q+QOYZtQJSGlFKUaBVNAAFoFkdAmYZ7gjyFwnV9lChoBmgJaA9DCKxT5XsGBXFAlIaUUpRoFU0aAWgWR0CZhy3Y+Sr6dX2UKGgGaAloD0MIKnReY5dbckCUhpRSlGgVTTYBaBZHQJmHRqWTouB1fZQoaAZoCWgPQwhKKH0h5DRvQJSGlFKUaBVNAgFoFkdAmYigy6+WW3V9lChoBmgJaA9DCJt0WyIXuHBAlIaUUpRoFU0LAWgWR0CZiUL5RCQcdX2UKGgGaAloD0MI0qdV9EfvcUCUhpRSlGgVTRgBaBZHQJmJUuUUwi91fZQoaAZoCWgPQwizQpHu5+9yQJSGlFKUaBVNHQFoFkdAmYo5HqeK9HV9lChoBmgJaA9DCBcs1QW8o3BAlIaUUpRoFUv5aBZHQJmKSgmJFb51fZQoaAZoCWgPQwiOPuYDgn9yQJSGlFKUaBVNCwFoFkdAmYppYPoV23V9lChoBmgJaA9DCHfaGhEMsW1AlIaUUpRoFU0jAWgWR0CZisCUornUdX2UKGgGaAloD0MIuynltZIJc0CUhpRSlGgVTQABaBZHQJmLK5vtMPB1fZQoaAZoCWgPQwhnmUUotpBxQJSGlFKUaBVNEwFoFkdAmYtJKODJ2nV9lChoBmgJaA9DCI/DYP4K7W5AlIaUUpRoFU0tAWgWR0CZi72saKk3dX2UKGgGaAloD0MI/pjWprHScUCUhpRSlGgVTQoBaBZHQJmM5utOmBR1fZQoaAZoCWgPQwhNaf0tgXNwQJSGlFKUaBVNKAFoFkdAmY0l8w5/9nV9lChoBmgJaA9DCHbAdcVMOXNAlIaUUpRoFU0QAWgWR0CZjm3ZPEbYdX2UKGgGaAloD0MIdJoF2h24cECUhpRSlGgVTTMBaBZHQJmOd9uxbB51fZQoaAZoCWgPQwgJTn0gufhwQJSGlFKUaBVNVwFoFkdAmY7UGu9vj3V9lChoBmgJaA9DCPse9ddr8XBAlIaUUpRoFU0mAWgWR0CZjuxVhkRSdX2UKGgGaAloD0MIn1kSoCZZcECUhpRSlGgVS/JoFkdAmY8I1DSgG3V9lChoBmgJaA9DCBWoxeDhdnNAlIaUUpRoFU0RAWgWR0CZkN4L1EmZdX2UKGgGaAloD0MIfc1y2Whab0CUhpRSlGgVTQMBaBZHQJmRl9ph4MZ1fZQoaAZoCWgPQwjNOuP74idwQJSGlFKUaBVL/2gWR0CZkb06YE4edX2UKGgGaAloD0MIdm9FYoI4c0CUhpRSlGgVTSIBaBZHQJmR3BnBciZ1fZQoaAZoCWgPQwibOSS1UDtsQJSGlFKUaBVNBQFoFkdAmaamI42jwnV9lChoBmgJaA9DCPziUpW2dnBAlIaUUpRoFU0lAWgWR0CZpolZX+2mdX2UKGgGaAloD0MIiWGHMWmxbUCUhpRSlGgVTRcBaBZHQJmmp/hESdx1fZQoaAZoCWgPQwgmpgux+v1OQJSGlFKUaBVLxmgWR0CZpxeGfwqidX2UKGgGaAloD0MItCCU9/GicECUhpRSlGgVTRwBaBZHQJmnTNorWiF1fZQoaAZoCWgPQwj356IhI6xwQJSGlFKUaBVNIgFoFkdAmafrtqpLmXV9lChoBmgJaA9DCPyPTIcOE3BAlIaUUpRoFU0GAWgWR0CZqGNayKNydX2UKGgGaAloD0MIZAeVuI7Bb0CUhpRSlGgVS/9oFkdAmao/tD2JznV9lChoBmgJaA9DCAk2rn+XMHFAlIaUUpRoFU0RAWgWR0CZqiUc4o7WdX2UKGgGaAloD0MItiv0wXIocUCUhpRSlGgVTRABaBZHQJmqmLdepn91fZQoaAZoCWgPQwiS7BFqhsRyQJSGlFKUaBVNJwFoFkdAmarNHc1wYXV9lChoBmgJaA9DCCLFAIkmwDBAlIaUUpRoFUvcaBZHQJmrOYkVvdd1fZQoaAZoCWgPQwhR9pZyfrlxQJSGlFKUaBVL/GgWR0CZrCNfgJkYdX2UKGgGaAloD0MIYRvxZDdccECUhpRSlGgVTWUBaBZHQJms7We6I311fZQoaAZoCWgPQwhoBYasboxtQJSGlFKUaBVL92gWR0CZrQouwosqdX2UKGgGaAloD0MI5ZttbowWckCUhpRSlGgVTUQBaBZHQJmtqcmShal1fZQoaAZoCWgPQwiILqhvmehvQJSGlFKUaBVNEQFoFkdAma3gg1WKdnV9lChoBmgJaA9DCJ7OFaVEznFAlIaUUpRoFU06AWgWR0CZrfqR2bG4dX2UKGgGaAloD0MIyQBQxU21cECUhpRSlGgVS/toFkdAma4VmSQo1HV9lChoBmgJaA9DCNuizAbZ33BAlIaUUpRoFUvraBZHQJmuV+WnjyZ1fZQoaAZoCWgPQwiAJy1c1rxxQJSGlFKUaBVL42gWR0CZrqJO32EkdX2UKGgGaAloD0MIhSaJJSXDcUCUhpRSlGgVTSABaBZHQJmuxznzQNV1fZQoaAZoCWgPQwgu4jsxa6JxQJSGlFKUaBVL+GgWR0CZsZovi97GdX2UKGgGaAloD0MIhSLdz+nQcECUhpRSlGgVTRABaBZHQJmxokE9t/F1fZQoaAZoCWgPQwgQkgVMoC9xQJSGlFKUaBVNHQFoFkdAmbIl2aDwpnV9lChoBmgJaA9DCM6luKqsoHFAlIaUUpRoFU0UAWgWR0CZsvWYF7ladX2UKGgGaAloD0MIXwzlRPvbcUCUhpRSlGgVTT4BaBZHQJmzkIRh+fB1fZQoaAZoCWgPQwi/u5UluqJvQJSGlFKUaBVNEQFoFkdAmbPt2HLzPXV9lChoBmgJaA9DCCLeOv/2X2xAlIaUUpRoFUv/aBZHQJm0Lfj0cwR1fZQoaAZoCWgPQwiKPbSPlUxwQJSGlFKUaBVNEwFoFkdAmbW3fl6qsHV9lChoBmgJaA9DCF9FRgckLG9AlIaUUpRoFU0NAWgWR0CZtdxLkCFLdX2UKGgGaAloD0MIZmzoZj/NcECUhpRSlGgVTS0BaBZHQJm11jSXt0F1fZQoaAZoCWgPQwh/3795cXRuQJSGlFKUaBVNIgFoFkdAmbZlzZHuqnV9lChoBmgJaA9DCJW4jnEFLHFAlIaUUpRoFU0NAWgWR0CZtk8wHqu9dX2UKGgGaAloD0MICtejcD2zc0CUhpRSlGgVTRoBaBZHQJm2ZNL127p1fZQoaAZoCWgPQwjqzD0kfFpvQJSGlFKUaBVNHAFoFkdAmbcw4sEq2HV9lChoBmgJaA9DCCVbXU4JjnFAlIaUUpRoFU0rAWgWR0CZt2eHSF4+dX2UKGgGaAloD0MI/dzQlJ0RcECUhpRSlGgVS+xoFkdAmbiX2mHgxnV9lChoBmgJaA9DCBq/8EpS7nFAlIaUUpRoFU0dAWgWR0CZupWI42jxdX2UKGgGaAloD0MImS1ZFWFJc0CUhpRSlGgVTQIBaBZHQJm7OWpqASZ1fZQoaAZoCWgPQwhhxhSscbRwQJSGlFKUaBVNQAFoFkdAmbs74rSVnnV9lChoBmgJaA9DCHi3skRnUm9AlIaUUpRoFU0jAWgWR0CZu6tNBWxRdX2UKGgGaAloD0MIe9egLz0wcECUhpRSlGgVTRMBaBZHQJm8W+36Q/51fZQoaAZoCWgPQwgplfCEXg1wQJSGlFKUaBVNLAFoFkdAmbzkzsQd0nV9lChoBmgJaA9DCOwVFtwPm3FAlIaUUpRoFUv6aBZHQJm9nqPfbbl1fZQoaAZoCWgPQwhzafzCK3dyQJSGlFKUaBVNDwFoFkdAmb3KQA+6iHV9lChoBmgJaA9DCC6NX3jlNHFAlIaUUpRoFUv8aBZHQJm9yLGaQV91fZQoaAZoCWgPQwgjowOSME9wQJSGlFKUaBVNCQFoFkdAmb4qYqoZRHV9lChoBmgJaA9DCDHRIAXP9XFAlIaUUpRoFU0aAWgWR0CZviYJmdy1dX2UKGgGaAloD0MIiXjr/FsgckCUhpRSlGgVTTUBaBZHQJm+rCP6sQx1fZQoaAZoCWgPQwgNHNDSlb5vQJSGlFKUaBVNAQFoFkdAmb7kojOcD3V9lChoBmgJaA9DCLoSgeqfZ3BAlIaUUpRoFU0aAWgWR0CZv0yyUs4DdX2UKGgGaAloD0MIqDRiZh9kcUCUhpRSlGgVTTEBaBZHQJnBVSiudPN1fZQoaAZoCWgPQwigh9o2TD5wQJSGlFKUaBVL8mgWR0CZwfdwvQF+dX2UKGgGaAloD0MIYW2MnfC4cUCUhpRSlGgVTQ4BaBZHQJnCPai9Iwx1fZQoaAZoCWgPQwgah/pdWARzQJSGlFKUaBVL8mgWR0CZwl6zmfXgdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 372, "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"}}
+{"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 0x7f76eae65ef0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f76eae65f80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f76eae6d050>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f76eae6d0e0>", "_build": "<function ActorCriticPolicy._build at 0x7f76eae6d170>", "forward": "<function ActorCriticPolicy.forward at 0x7f76eae6d200>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f76eae6d290>", "_predict": "<function ActorCriticPolicy._predict at 0x7f76eae6d320>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f76eae6d3b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f76eae6d440>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f76eae6d4d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f76eaeb2990>"}, "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": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651691453.2175567, "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": -0.004885333333333408, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 368, "n_steps": 1024, "gamma": 0.9999, "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"}}

ppo-LunarLander-1mil-default-params.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1476c1e9b7e2d05a72c1f6d9167bd84ee3202f8af0187370e1676590accd7a00
-size 144082
+oid sha256:73732aed292a0909aa3de85f274f07baf607cf5590561c94b4e49bb0cb52a2a5
+size 144095

ppo-LunarLander-1mil-default-params/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 1507328,
+    "_total_timesteps": 1500000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1651690340.8516178,
+    "start_time": 1651691453.2175567,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,18 +66,18 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.015808000000000044,
+    "_current_progress_remaining": -0.004885333333333408,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 372,
+    "_n_updates": 368,
     "n_steps": 1024,
-    "gamma": 0.999,
+    "gamma": 0.9999,
     "gae_lambda": 0.98,
     "ent_coef": 0.01,
     "vf_coef": 0.5,

ppo-LunarLander-1mil-default-params/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f7c5278b5ea5f72eae912a3861c580c18ed259af43217d08faba6ca07efff894
+oid sha256:a5929aa760160283db94fd9d555bfd4f15dadc10c5a56070ee3e1d1c5f46df9a
 size 84893

ppo-LunarLander-1mil-default-params/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fc79194652b5803c5b5c7e8ede4fd9a9502d3f0458ec11751bb7047a37cb6511
+oid sha256:b2af40b6c0ce20713512a2fa7a7adf1f52e4e28df5fc70bbd9ad7cab649069e4
 size 43201

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6e15adf143cc7e695f3b595a8a7da9830114c9155049f79b8ee14fdb245dd982
-size 204583
+oid sha256:35f313342778515fee1ea7c22dafaa429884335b2db45448410034f63c203088
+size 194327

results.json

@@ -1 +1 @@
-{"mean_reward": 265.768869464821, "std_reward": 20.872864726210814, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-04T19:09:09.207481"}
+{"mean_reward": 261.24144552710015, "std_reward": 15.43812150180726, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-04T19:40:58.069079"}