Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 279.93 +/- 9.51
+      value: -51.80 +/- 74.54
       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 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 0x7f815eac4160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f815eac41f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f815eac4280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f815eac4310>", "_build": "<function ActorCriticPolicy._build at 0x7f815eac43a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f815eac4430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f815eac44c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f815eac4550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f815eac45e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f815eac4670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f815eac4700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f815eabf600>"}, "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": 16384, "_total_timesteps": 100, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670321521865615216, "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": -162.84, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 252, "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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+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 0x7f10b2f6c160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f10b2f6c1f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f10b2f6c280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f10b2f6c310>", "_build": "<function ActorCriticPolicy._build at 0x7f10b2f6c3a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f10b2f6c430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f10b2f6c4c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f10b2f6c550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f10b2f6c5e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f10b2f6c670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f10b2f6c700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f10b2f67600>"}, "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": 16384, "_total_timesteps": 1000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670325020652675323, "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": -15.384, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 8, "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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d5fd0217563eaca73f38da303d1de27738b5fde017b46d8242b3eb8b9005f0b3
-size 144742
+oid sha256:aa3464da58b6b6fe0662161a1be626ce20e8d577ffec0c52d19dfb4196a10c08
+size 147001

ppo-LunarLander-v2/data

@@ -4,19 +4,19 @@
         ":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 0x7f815eac4160>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f815eac41f0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f815eac4280>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f815eac4310>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f815eac43a0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f815eac4430>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f815eac44c0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f815eac4550>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f815eac45e0>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f815eac4670>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f815eac4700>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f10b2f6c160>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f10b2f6c1f0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f10b2f6c280>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f10b2f6c310>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f10b2f6c3a0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f10b2f6c430>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f10b2f6c4c0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f10b2f6c550>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f10b2f6c5e0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f10b2f6c670>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f10b2f6c700>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f815eabf600>"
+        "_abc_impl": "<_abc_data object at 0x7f10b2f67600>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -43,11 +43,11 @@
     },
     "n_envs": 16,
     "num_timesteps": 16384,
-    "_total_timesteps": 100,
+    "_total_timesteps": 1000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1670321521865615216,
+    "start_time": 1670325020652675323,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAM1Jo72m6oY/gkBtvmyx/L6R8xq+WGeWvAAAAAAAAAAAM4iVPObUgj9jzlQ90PoRvyS2jTzWbMY9AAAAAAAAAADmUUO9NbqwP2BJsL7Pb4S+wNX9vKDygb4AAAAAAAAAAKYuxb0m9bE/PiADv4buib5Pjs+9ctifvgAAAAAAAAAAOhfMPojqRT/mxKG8ypQDv/8Hoz6X7xK+AAAAAAAAAACqrme+XJt7P99Byr4y+uq+HoTLvgI9Zr0AAAAAAAAAADPt+jy5Mqw/hd6ZPk/Y3L61sAU9KqpePgAAAAAAAAAAMzu4O7jWorm9OFg6OlkZNn0M/rjJ+4C5AACAPwAAgD9mloO6rvOMukIQ27YALrEwTvghu07n9zUAAIA/AACAPwB1G73Dqjs7DOHCvQV+qb3BAQK9BwiaPgAAgD8AAAAAYFwyPgRobz4yoKS+DOKDvjaG1Tw207e9AAAAAAAAAAD6tiM+bNIrP+bHCr5Fuui+3RQCPiMsV70AAAAAAAAAAM1Yi7uFe8C5ci5+tcm32rDig9s7UMG+NAAAgD8AAIA/oPYAvo1tkD99R/i+BoP7vpg0EL6KpGm+AAAAAAAAAABanUu+Hr4iP6KS8T2jYrm+/kUwvnrdAT4AAAAAAAAAAJo/sTyJSkQ9SxgEvjF8fb6qLCe9JkWuvAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,16 +66,16 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -162.84,
+    "_current_progress_remaining": -15.384,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "gAWVfQkAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI19mQf2bSUECUhpRSlIwBbJRLr4wBdJRHQMA+eGV7hNx1fZQoaAZoCWgPQwh2NXnKqrdxQJSGlFKUaBVL02gWR0DAPp0rTYukdX2UKGgGaAloD0MIcTjzq/k4c0CUhpRSlGgVS99oFkdAwD6q46Oo53V9lChoBmgJaA9DCBUb8zpiaHFAlIaUUpRoFUvmaBZHQMA+snXumaZ1fZQoaAZoCWgPQwgxI7w9iK1wQJSGlFKUaBVL6WgWR0DAPrVchTwVdX2UKGgGaAloD0MImUf+YCAocUCUhpRSlGgVS+loFkdAwD61QpF1CHV9lChoBmgJaA9DCIknu5nRyG1AlIaUUpRoFUv1aBZHQMA+wQeFL391fZQoaAZoCWgPQwjRXRJnBUVxQJSGlFKUaBVL+mgWR0DAPsWc8TzvdX2UKGgGaAloD0MIqODwgshDcUCUhpRSlGgVTQkBaBZHQMA+0sPJ7sx1fZQoaAZoCWgPQwi+iSE5mTJuQJSGlFKUaBVNDAFoFkdAwD7VSOzY3HV9lChoBmgJaA9DCJsBLsiWkm5AlIaUUpRoFU0WAWgWR0DAPtylchTwdX2UKGgGaAloD0MIkzZV98h/cECUhpRSlGgVTSIBaBZHQMA+5h2OhkB1fZQoaAZoCWgPQwhbBpylJOJxQJSGlFKUaBVNNgFoFkdAwD71ixVyWHV9lChoBmgJaA9DCM2QKoqX9nFAlIaUUpRoFU09AWgWR0DAPvsETxoadX2UKGgGaAloD0MIG9XpQNa+ckCUhpRSlGgVTWABaBZHQMA/FpNj9XN1fZQoaAZoCWgPQwjNPLmmQANwQJSGlFKUaBVNswFoFkdAwD9bORkmQnV9lChoBmgJaA9DCLFuvDuyHnFAlIaUUpRoFUvvaBZHQMA/aKG+K0l1fZQoaAZoCWgPQwgs2EY8WblyQJSGlFKUaBVNJAFoFkdAwD94oKlYU3V9lChoBmgJaA9DCO+pnPYU0W5AlIaUUpRoFUvuaBZHQMA/iN52Qnx1fZQoaAZoCWgPQwhI/fUKCyJwQJSGlFKUaBVNCAFoFkdAwD+NXgccVHV9lChoBmgJaA9DCLBx/bs+7W9AlIaUUpRoFUvsaBZHQMA/mloUSIx1fZQoaAZoCWgPQwga+FENuzRwQJSGlFKUaBVL32gWR0DAP5oNAkcCdX2UKGgGaAloD0MIlX1XBP/bcUCUhpRSlGgVS/xoFkdAwD+bQ3xWk3V9lChoBmgJaA9DCGglrfgGT3NAlIaUUpRoFU0YAWgWR0DAP6Ql2NeddX2UKGgGaAloD0MIMV2I1d8Fc0CUhpRSlGgVTSMBaBZHQMA/qu8TSLJ1fZQoaAZoCWgPQwgwRiQKLRBxQJSGlFKUaBVL7GgWR0DAP65KaodddX2UKGgGaAloD0MI4dIx55ksb0CUhpRSlGgVS+JoFkdAwD+7N+so2HV9lChoBmgJaA9DCMNF7ulqb3FAlIaUUpRoFU0YAWgWR0DAP79tO2y+dX2UKGgGaAloD0MIWWyTikb9cECUhpRSlGgVS/NoFkdAwD/COFQEZHV9lChoBmgJaA9DCOz4LxCEL25AlIaUUpRoFU1BAWgWR0DAP8L0jC53dX2UKGgGaAloD0MIYaQXtXvZcUCUhpRSlGgVTRoBaBZHQMA/94ku6Et1fZQoaAZoCWgPQwjNc0S+yy1zQJSGlFKUaBVL1mgWR0DAQDPeYUnHdX2UKGgGaAloD0MIprc/Fw0mckCUhpRSlGgVTQsBaBZHQMBARI/zJ6p1fZQoaAZoCWgPQwhw7NlzmWJtQJSGlFKUaBVNCgFoFkdAwEBUhIOH33V9lChoBmgJaA9DCAkWhzO/JnFAlIaUUpRoFUv9aBZHQMBAV/wiJO51fZQoaAZoCWgPQwhp5V5gVrZwQJSGlFKUaBVL9mgWR0DAQGJx3mmtdX2UKGgGaAloD0MIgUI9fcRwcUCUhpRSlGgVS/doFkdAwEBkJokAxXV9lChoBmgJaA9DCFjhlo9k03BAlIaUUpRoFUvwaBZHQMBAbrRKHwh1fZQoaAZoCWgPQwghIF9CBQtyQJSGlFKUaBVL22gWR0DAQHif4AS4dX2UKGgGaAloD0MIk8SScvdecECUhpRSlGgVS+toFkdAwEB9J5E+gXV9lChoBmgJaA9DCPxtT5DY8W9AlIaUUpRoFU0VAWgWR0DAQIb9ycTbdX2UKGgGaAloD0MIigW+oltkckCUhpRSlGgVTQgBaBZHQMBAht0/4Zd1fZQoaAZoCWgPQwjlRSbgl5ZyQJSGlFKUaBVL9WgWR0DAQIpbjcVQdX2UKGgGaAloD0MIG53zUxxpckCUhpRSlGgVTW0BaBZHQMBAjzF2mpF1fZQoaAZoCWgPQwgUsYhhB+dwQJSGlFKUaBVNXgFoFkdAwECyiaiKznV9lChoBmgJaA9DCOdtbHakQXBAlIaUUpRoFU04AWgWR0DAQLzpzLfUdX2UKGgGaAloD0MIdR4V/3c3b0CUhpRSlGgVTQoBaBZHQMBA1jSG8Ep1fZQoaAZoCWgPQwhwmdNlMRRzQJSGlFKUaBVL32gWR0DAQPZtix3WdX2UKGgGaAloD0MIOZ1kq0tnc0CUhpRSlGgVS/JoFkdAwED5ddmg8XV9lChoBmgJaA9DCLTKTGn96m9AlIaUUpRoFUvXaBZHQMBA/SvcJt11fZQoaAZoCWgPQwhodXKGYptuQJSGlFKUaBVL6WgWR0DAQRl74SHudX2UKGgGaAloD0MI3lZ6bbZDb0CUhpRSlGgVS+xoFkdAwEEdqLS/kHV9lChoBmgJaA9DCFJ/vcJCMHBAlIaUUpRoFU0CAWgWR0DAQSYplSTAdX2UKGgGaAloD0MIaFpiZTQXcECUhpRSlGgVS+ZoFkdAwEEs/M4cWHV9lChoBmgJaA9DCJQVw9WBkm9AlIaUUpRoFUvXaBZHQMBBMW0iQkp1fZQoaAZoCWgPQwhZhc0A1+dwQJSGlFKUaBVL/GgWR0DAQTVBF/hEdX2UKGgGaAloD0MI3NYWntfIcECUhpRSlGgVS9hoFkdAwEE3SuyNXHVlLg=="
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 252,
+    "_n_updates": 8,
     "n_steps": 1024,
     "gamma": 0.999,
     "gae_lambda": 0.98,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6ce19d8ed4e314d4522b20eb7b28b44e247f57d6658167f1356383069941ccfb
+oid sha256:ebfb3b840d38cb038b3b1606a323151c457f8e7e06fde81b76345daa9b5c1e29
 size 87865

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:92856e8bf2d2c502c9e476ceb57cc6c923bd456ecfad3e30afa08b19d6c358f8
+oid sha256:612d5966b84a7bf44b958d216234f2796a26cb0cb4259c9c9df48f9b3f91acb8
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": 279.92999744490413, "std_reward": 9.512599280667937, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-06T10:14:40.183310"}
+{"mean_reward": -51.803402819857, "std_reward": 74.5394668582628, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-06T11:11:53.244741"}