Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 234.79 +/- 70.34
+      value: 264.56 +/- 16.65
       name: mean_reward
       verified: false
 ---

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 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 0x7f23c2d7c160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f23c2d7c1f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f23c2d7c280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f23c2d7c310>", "_build": "<function ActorCriticPolicy._build at 0x7f23c2d7c3a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f23c2d7c430>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f23c2d7c4c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f23c2d7c550>", "_predict": "<function ActorCriticPolicy._predict at 0x7f23c2d7c5e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f23c2d7c670>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f23c2d7c700>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f23c2d7c790>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f23c2d777b0>"}, "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": 1675620005421511847, "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": 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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "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 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 0x7f1ee0213a60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1ee0213af0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1ee0213b80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1ee0213c10>", "_build": "<function ActorCriticPolicy._build at 0x7f1ee0213ca0>", "forward": "<function ActorCriticPolicy.forward at 0x7f1ee0213d30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f1ee0213dc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1ee0213e50>", "_predict": "<function ActorCriticPolicy._predict at 0x7f1ee0213ee0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1ee0213f70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1ee0217040>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1ee02170d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f1ee020be40>"}, "verbose": 0, "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": 1675649790659222343, "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:": "gAWVMxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIZ3+g3LbTbECUhpRSlIwBbJRL7IwBdJRHQJobyphnanJ1fZQoaAZoCWgPQwiJeOv8G9VwQJSGlFKUaBVL2mgWR0CaG/cWTHKfdX2UKGgGaAloD0MIj9/b9OcpcUCUhpRSlGgVS/5oFkdAmh1S9du50HV9lChoBmgJaA9DCIC21axzdHFAlIaUUpRoFUv6aBZHQJoiUC5mRNh1fZQoaAZoCWgPQwic+6vHvZxxQJSGlFKUaBVL/GgWR0CaIlGR3eN2dX2UKGgGaAloD0MIccgG0gU0cUCUhpRSlGgVS+1oFkdAmiJ3V09yLnV9lChoBmgJaA9DCCI3ww34VmxAlIaUUpRoFUvkaBZHQJoinZ5AyEd1fZQoaAZoCWgPQwi5Fi1AWxZwQJSGlFKUaBVL9mgWR0CaIrDs+mm+dX2UKGgGaAloD0MIdt8xPHaSYECUhpRSlGgVTegDaBZHQJoi8pEx7At1fZQoaAZoCWgPQwh5dY4B2fVuQJSGlFKUaBVL2mgWR0CaI1MfzSThdX2UKGgGaAloD0MI1Ce5w6YCbkCUhpRSlGgVS9xoFkdAmiQ96HCXQnV9lChoBmgJaA9DCAQg7uqVInFAlIaUUpRoFUv0aBZHQJok4FTvRZ51fZQoaAZoCWgPQwgQCHQm7fhtQJSGlFKUaBVL+WgWR0CaJPqLS/j9dX2UKGgGaAloD0MIYtuizEaWcUCUhpRSlGgVS+VoFkdAmiXN1U2kz3V9lChoBmgJaA9DCOW36GSpX15AlIaUUpRoFU3oA2gWR0CaJoJk5IYndX2UKGgGaAloD0MIT3gJTv3/YkCUhpRSlGgVTegDaBZHQJonsHNX5nF1fZQoaAZoCWgPQwiXcr7YeyJyQJSGlFKUaBVL0mgWR0CaKVEs8PnTdX2UKGgGaAloD0MI9yAE5AsVcECUhpRSlGgVS9ZoFkdAmimHkkrwv3V9lChoBmgJaA9DCPvOL0oQYHJAlIaUUpRoFUvbaBZHQJoqPxVhkRV1fZQoaAZoCWgPQwhNSkG3ly1uQJSGlFKUaBVL4WgWR0CaKjyI55qudX2UKGgGaAloD0MI46dxb36Zb0CUhpRSlGgVS+5oFkdAmiqgHJLdvnV9lChoBmgJaA9DCA05tp4hLWFAlIaUUpRoFU3oA2gWR0CaKvg75mAcdX2UKGgGaAloD0MI275H/TVOcUCUhpRSlGgVTQoBaBZHQJosIFSsKb91fZQoaAZoCWgPQwj1E85uLX5xQJSGlFKUaBVL/mgWR0CaLJoS+QEIdX2UKGgGaAloD0MIJEVkWAXfcECUhpRSlGgVTQcBaBZHQJothM/QjUx1fZQoaAZoCWgPQwjDmsqicKVxQJSGlFKUaBVL3WgWR0CaLdhDw6QvdX2UKGgGaAloD0MIJZLoZZTKbUCUhpRSlGgVTRIBaBZHQJot9N7Bwdd1fZQoaAZoCWgPQwjZJaq3hqhxQJSGlFKUaBVL0WgWR0CaLpy/KyOadX2UKGgGaAloD0MIL/fJUYCdY0CUhpRSlGgVTegDaBZHQJowVjriVB51fZQoaAZoCWgPQwj/6Js0jfFvQJSGlFKUaBVL5mgWR0CaMNa0x/NJdX2UKGgGaAloD0MIHPD5YYQWcECUhpRSlGgVS+VoFkdAmjDvHo5ggHV9lChoBmgJaA9DCDuPiv97dXBAlIaUUpRoFUvkaBZHQJoxhksjFAF1fZQoaAZoCWgPQwh9XYb/dAJyQJSGlFKUaBVL4WgWR0CaMhh24d6tdX2UKGgGaAloD0MIgh3/BQJacECUhpRSlGgVS/JoFkdAmjJNTxXnyXV9lChoBmgJaA9DCJqYLsSqtnJAlIaUUpRoFUv9aBZHQJoyTkS26TZ1fZQoaAZoCWgPQwjerwJ8d/1wQJSGlFKUaBVL7WgWR0CaNByv9tMxdX2UKGgGaAloD0MIqRH6mXricUCUhpRSlGgVS9loFkdAmjReS4e9z3V9lChoBmgJaA9DCD1JumbydHFAlIaUUpRoFU0IAWgWR0CaNHyMDOkddX2UKGgGaAloD0MIc3/1uG8mbkCUhpRSlGgVS95oFkdAmjTuhCdBjXV9lChoBmgJaA9DCPWidr8K6G9AlIaUUpRoFUvkaBZHQJo1ACgbp/x1fZQoaAZoCWgPQwgP1v85TElhQJSGlFKUaBVN6ANoFkdAmjUmozeoDXV9lChoBmgJaA9DCNeJy/EKnHBAlIaUUpRoFU0QAWgWR0CaNugrpaA4dX2UKGgGaAloD0MIX7THCylUcECUhpRSlGgVS9ZoFkdAmjden/DLsHV9lChoBmgJaA9DCNV2E3xTt29AlIaUUpRoFUvjaBZHQJo3rMB6rvN1fZQoaAZoCWgPQwh4X5ULlbVwQJSGlFKUaBVNAAFoFkdAmjgUwN9YwXV9lChoBmgJaA9DCNh9x/DYwG1AlIaUUpRoFUvlaBZHQJo5pz/6wdN1fZQoaAZoCWgPQwj3dktywIJuQJSGlFKUaBVL6GgWR0CaOctj0+TvdX2UKGgGaAloD0MIX3tmSYDgcUCUhpRSlGgVTQQBaBZHQJo57/tIClt1fZQoaAZoCWgPQwizKOyiKARwQJSGlFKUaBVL1WgWR0CaO20DEFW5dX2UKGgGaAloD0MIFcRA1z40cUCUhpRSlGgVTSMBaBZHQJo8A7yQPqd1fZQoaAZoCWgPQwgmw/F8xmNxQJSGlFKUaBVL52gWR0CaPH9gWrOrdX2UKGgGaAloD0MILbKd76duc0CUhpRSlGgVS+VoFkdAmjyUoa1kUnV9lChoBmgJaA9DCF02OufnZ3BAlIaUUpRoFUvpaBZHQJo9qR/3Fkx1fZQoaAZoCWgPQwgUsB2MGENxQJSGlFKUaBVL/mgWR0CaPkhXr+o+dX2UKGgGaAloD0MI8dk6OJhJcECUhpRSlGgVS+RoFkdAmkBMtf5ULnV9lChoBmgJaA9DCJIhx9YzwW9AlIaUUpRoFUvZaBZHQJpA6925hBt1fZQoaAZoCWgPQwgPQ6uTc81xQJSGlFKUaBVNFgFoFkdAmkPCWRigCnV9lChoBmgJaA9DCA+Yh0z5lm9AlIaUUpRoFUvgaBZHQJpEDcWTHKh1fZQoaAZoCWgPQwjZ7h6gez5tQJSGlFKUaBVL7GgWR0CaRRrlNlAedX2UKGgGaAloD0MIvVXXoZoub0CUhpRSlGgVTR8BaBZHQJpFprqMWGh1fZQoaAZoCWgPQwgjgnFwqSRyQJSGlFKUaBVL/WgWR0CaRdmzjWCmdX2UKGgGaAloD0MI9yLajimGb0CUhpRSlGgVS+JoFkdAmkcghbGFSXV9lChoBmgJaA9DCF71gHnItGFAlIaUUpRoFU3oA2gWR0CaR245cTrWdX2UKGgGaAloD0MIwtzu5b6BcECUhpRSlGgVS/poFkdAmkejw6QvH3V9lChoBmgJaA9DCLmmQGZnh21AlIaUUpRoFUviaBZHQJpHuMBIWgx1fZQoaAZoCWgPQwgEIVnABOpuQJSGlFKUaBVL8GgWR0CaSGBlMAWBdX2UKGgGaAloD0MI5PVgUvw2cECUhpRSlGgVS/JoFkdAmkmY/NZ/1HV9lChoBmgJaA9DCBu62R+orXFAlIaUUpRoFUv5aBZHQJpKjL8rI5p1fZQoaAZoCWgPQwiCj8GKU9hgQJSGlFKUaBVN6ANoFkdAmkueE/Spi3V9lChoBmgJaA9DCF1PdF14bXNAlIaUUpRoFUvgaBZHQJpL4xtYSxt1fZQoaAZoCWgPQwhq9dVVQaxyQJSGlFKUaBVL7mgWR0CaS/Jvo/zKdX2UKGgGaAloD0MI93XgnBFkcUCUhpRSlGgVS+RoFkdAmk4ayOaOP3V9lChoBmgJaA9DCCZV203w+m9AlIaUUpRoFUvyaBZHQJpOY5MlC1J1fZQoaAZoCWgPQwhDOGbZUzhwQJSGlFKUaBVL42gWR0CaTwEw35vcdX2UKGgGaAloD0MIzk9xHPjwcECUhpRSlGgVS/hoFkdAmk8/giu+y3V9lChoBmgJaA9DCMcqpWc6OnJAlIaUUpRoFUvWaBZHQJpPlRyfcvd1fZQoaAZoCWgPQwiNl24Sg7ptQJSGlFKUaBVL+2gWR0CaT6RDTjNqdX2UKGgGaAloD0MIpFGBk214ckCUhpRSlGgVS+hoFkdAmk/nyZrpJXV9lChoBmgJaA9DCFw+kpJeXnBAlIaUUpRoFUvfaBZHQJpQBTHbRF91fZQoaAZoCWgPQwhftwiMtXtyQJSGlFKUaBVL82gWR0CaUHZl4C6pdX2UKGgGaAloD0MICMvY0A0OcUCUhpRSlGgVS91oFkdAmlHDvJA+p3V9lChoBmgJaA9DCNVBXg9mo3BAlIaUUpRoFU0EAWgWR0CaUjrMTviMdX2UKGgGaAloD0MIxR9FnTkxcUCUhpRSlGgVS9poFkdAmlKq1Cw8n3V9lChoBmgJaA9DCJlIaTbPzXBAlIaUUpRoFUv3aBZHQJpTURRMvh91fZQoaAZoCWgPQwhtjQjGwdNyQJSGlFKUaBVNBwFoFkdAmlP6sZHd43V9lChoBmgJaA9DCOdz7nY9y3JAlIaUUpRoFUvdaBZHQJpU3M+u/1x1fZQoaAZoCWgPQwhmEB/YcTlvQJSGlFKUaBVL82gWR0CaVUDlHSWrdX2UKGgGaAloD0MIhWBVvby1cECUhpRSlGgVS+FoFkdAmlXqvNeMQ3V9lChoBmgJaA9DCNcWnpcKhnJAlIaUUpRoFUvbaBZHQJpWdeJHiFV1fZQoaAZoCWgPQwj84lKVNlNxQJSGlFKUaBVL+mgWR0CaVnrWiDdydX2UKGgGaAloD0MIzVfJx243bUCUhpRSlGgVS/JoFkdAmlbhYV6/qXV9lChoBmgJaA9DCFVRvMqas3BAlIaUUpRoFUvuaBZHQJpXKo/A0sR1fZQoaAZoCWgPQwgiUtMuJkdwQJSGlFKUaBVL4WgWR0CaWNg13t8edX2UKGgGaAloD0MI8FLqkjGycECUhpRSlGgVS85oFkdAmlk1y7wrlXV9lChoBmgJaA9DCMQHdvxX93FAlIaUUpRoFUvnaBZHQJpZm7ROUMZ1fZQoaAZoCWgPQwirI0c6A9ZfQJSGlFKUaBVN6ANoFkdAmlqN6gM+eXV9lChoBmgJaA9DCJBKsaNxyGxAlIaUUpRoFU1EAWgWR0CaWqg88s+WdX2UKGgGaAloD0MI6zpUUxJvbkCUhpRSlGgVS+1oFkdAmlsDIq9XcXV9lChoBmgJaA9DCMK9Mm+VvHBAlIaUUpRoFUvuaBZHQJpbtXjlxOt1fZQoaAZoCWgPQwhaSwFpf0VuQJSGlFKUaBVL5WgWR0CaXFUQCjk/dWUu"}, "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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

my_ship.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:78379ec598801c014ec023e6ce5bfe05f3eb0fb98e667a5d15f5655ab624b764
-size 147379
+oid sha256:aa788751691637c3d361dad774a5587c20572a7bd303961d990c0b280ed3e882
+size 147319

my_ship/data

@@ -4,22 +4,22 @@
         ":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 0x7f23c2d7c160>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f23c2d7c1f0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f23c2d7c280>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f23c2d7c310>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f23c2d7c3a0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f23c2d7c430>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f23c2d7c4c0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f23c2d7c550>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f23c2d7c5e0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f23c2d7c670>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f23c2d7c700>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f23c2d7c790>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f1ee0213a60>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1ee0213af0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1ee0213b80>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1ee0213c10>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f1ee0213ca0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f1ee0213d30>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f1ee0213dc0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1ee0213e50>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f1ee0213ee0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1ee0213f70>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1ee0217040>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1ee02170d0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f23c2d777b0>"
+        "_abc_impl": "<_abc_data object at 0x7f1ee020be40>"
     },
-    "verbose": 1,
+    "verbose": 0,
     "policy_kwargs": {},
     "observation_space": {
         ":type:": "<class 'gym.spaces.box.Box'>",
@@ -48,16 +48,16 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1675620005421511847,
+    "start_time": 1675649790659222343,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -70,7 +70,7 @@
     "_current_progress_remaining": -0.015808000000000044,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
@@ -87,7 +87,7 @@
     "n_epochs": 10,
     "clip_range": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "clip_range_vf": null,
     "normalize_advantage": true,

my_ship/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d3eb9febaaf0a169855482013e93370c13a0c295f8585b5129c92484e1f8b0af
+oid sha256:079bfc5483e94725207f1f20fbdf32ec637c48e8b9de1cc7ca5bb675208c633e
 size 87929

my_ship/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e81d11ee633d6877c36d3746d6ecf22a6fed6ee16e6d3f82d9f72068d099def9
+oid sha256:aeb887efa995e4d0d3d64fdf32efd0f48c4b5c733f6da345391f2ad91a5fbd06
 size 43393

results.json

@@ -1 +1 @@
-{"mean_reward": 234.7875118360294, "std_reward": 70.34140524705522, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-05T18:32:46.677253"}
+{"mean_reward": 264.5579368563768, "std_reward": 16.65003646589698, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-06T02:44:30.813657"}