PPO more timesteps

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -64.43 +/- 104.31
+      value: 262.59 +/- 14.26
       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 0x7f5cd150e9d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5cd150ea60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5cd150eaf0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5cd150eb80>", "_build": "<function ActorCriticPolicy._build at 0x7f5cd150ec10>", "forward": "<function ActorCriticPolicy.forward at 0x7f5cd150eca0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5cd150ed30>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5cd150edc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5cd150ee50>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5cd150eee0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5cd150ef70>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f5cd150a720>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 114688, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670423730296094575, "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": -0.1468799999999999, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 28, "n_steps": 1024, "gamma": 0.998, "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 0x7f5cd150e9d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5cd150ea60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5cd150eaf0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5cd150eb80>", "_build": "<function ActorCriticPolicy._build at 0x7f5cd150ec10>", "forward": "<function ActorCriticPolicy.forward at 0x7f5cd150eca0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5cd150ed30>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5cd150edc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5cd150ee50>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5cd150eee0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5cd150ef70>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f5cd150a720>"}, "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": 1670424010565570947, "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": 276, "n_steps": 1024, "gamma": 0.998, "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"}}

dqn-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:634b8531e3688242b30370748d31aafebbdf6966598c3fc43ff6f236d5b0a7b5
-size 147017
+oid sha256:1744d0e30bd2f0b0625f0dfc03a2351fd4037242a533dfdfcfe8e6dfeebb6124
+size 147118

dqn-LunarLander-v2/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 114688,
-    "_total_timesteps": 100000,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1670423730296094575,
+    "start_time": 1670424010565570947,
     "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'>",
@@ -66,16 +66,16 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.1468799999999999,
+    "_current_progress_remaining": -0.015808000000000044,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIJCnpYWhFUMCUhpRSlIwBbJRLX4wBdJRHQFX9yaNMoMN1fZQoaAZoCWgPQwgDQBU3bh9DwJSGlFKUaBVLimgWR0BV/sZ9/jKgdX2UKGgGaAloD0MIQswlVduvXsCUhpRSlGgVS29oFkdAVf+WZ7Xxv3V9lChoBmgJaA9DCDHRIAXPXmHAlIaUUpRoFUtraBZHQFYAt3fQ8fV1fZQoaAZoCWgPQwhZT62+ujVZwJSGlFKUaBVLW2gWR0BWAkKJEYwZdX2UKGgGaAloD0MI+kMzT67p8D+UhpRSlGgVS4poFkdAVgXZxrBTGnV9lChoBmgJaA9DCBFTIole01nAlIaUUpRoFUtjaBZHQFYGcqe9SMt1fZQoaAZoCWgPQwgk06HT86xZwJSGlFKUaBVLb2gWR0BWBiKaXrt3dX2UKGgGaAloD0MIrp0oCYlCS8CUhpRSlGgVS2doFkdAVggnTiKiwnV9lChoBmgJaA9DCAwgfCjReFzAlIaUUpRoFUtEaBZHQFYJOFQEZBN1fZQoaAZoCWgPQwjMfXIUIFhXwJSGlFKUaBVLQmgWR0BWClc2R7qqdX2UKGgGaAloD0MIHxK+9zdOasCUhpRSlGgVS3RoFkdAVgtZIQOFxnV9lChoBmgJaA9DCKVL/5JUrVXAlIaUUpRoFUteaBZHQFYLeoUBXCF1fZQoaAZoCWgPQwhO7+L9uI1YwJSGlFKUaBVLVmgWR0BWC/Tw2ETQdX2UKGgGaAloD0MI+Ki/XmH6UsCUhpRSlGgVS0xoFkdAVhLVZs9B8nV9lChoBmgJaA9DCG5RZoNM1knAlIaUUpRoFUtFaBZHQFYSsiSq2jR1fZQoaAZoCWgPQwh3vp8aL9BZwJSGlFKUaBVLeGgWR0BWE3hOxjaxdX2UKGgGaAloD0MIdqimJOuvV8CUhpRSlGgVS2FoFkdAVhXhZQpF1HV9lChoBmgJaA9DCEXZW8r5zk7AlIaUUpRoFUtgaBZHQFYWcawUxmF1fZQoaAZoCWgPQwiQSrGj8XNgwJSGlFKUaBVLa2gWR0BWFxK15Sm7dX2UKGgGaAloD0MIcAZ/v5hEU8CUhpRSlGgVS0FoFkdAVhgUQCjk/HV9lChoBmgJaA9DCMIwYMlVsWXAlIaUUpRoFUtvaBZHQFYYQsPJ7sx1fZQoaAZoCWgPQwgLJZNTO+tWwJSGlFKUaBVLVGgWR0BWGWVqveP8dX2UKGgGaAloD0MICDvFqkFYV8CUhpRSlGgVS09oFkdAVhpHUc4o7XV9lChoBmgJaA9DCIz1DUxuylPAlIaUUpRoFUtHaBZHQFYbgSvkill1fZQoaAZoCWgPQwgofSHkvEhZwJSGlFKUaBVLTmgWR0BWHSPdVNpNdX2UKGgGaAloD0MIBYpYxLCBVcCUhpRSlGgVS05oFkdAVh2ii7Ciy3V9lChoBmgJaA9DCOihtg2jZ1XAlIaUUpRoFUtuaBZHQFYfxM36yjZ1fZQoaAZoCWgPQwiN0qV/Sb5UwJSGlFKUaBVLYWgWR0BWIKbz9S/CdX2UKGgGaAloD0MIGQKAY88cXsCUhpRSlGgVS4FoFkdAViOV1Oj7AXV9lChoBmgJaA9DCLovZ7YrOlLAlIaUUpRoFUtKaBZHQFYktALRa5h1fZQoaAZoCWgPQwh/h6JAn8xKwJSGlFKUaBVLVmgWR0BWJru2JBPbdX2UKGgGaAloD0MI1QRR9wFcOcCUhpRSlGgVS0toFkdAVidqpLmITHV9lChoBmgJaA9DCCFX6lkQhE7AlIaUUpRoFUtKaBZHQFYnvvBrN4Z1fZQoaAZoCWgPQwhnCwith5hUwJSGlFKUaBVLSmgWR0BWKFYEGJN1dX2UKGgGaAloD0MI9WbUfJVYUcCUhpRSlGgVS0toFkdAVimkoF3Y+XV9lChoBmgJaA9DCMbBpWPOa1bAlIaUUpRoFUtlaBZHQFYqXN1QqI91fZQoaAZoCWgPQwi0WfW52gxSwJSGlFKUaBVLUWgWR0BWKt03fhuPdX2UKGgGaAloD0MIq8yU1t8+PMCUhpRSlGgVS1hoFkdAVi51U2kzoHV9lChoBmgJaA9DCC2UTE7tilTAlIaUUpRoFUtfaBZHQFYvOwxFiKB1fZQoaAZoCWgPQwhXYMjqVq8lwJSGlFKUaBVLYWgWR0BWM6cNH6MzdX2UKGgGaAloD0MILxSwHYyWXMCUhpRSlGgVS25oFkdAVjT/p+tr9HV9lChoBmgJaA9DCIHrihnhT0TAlIaUUpRoFUtvaBZHQFY3ptaY/ml1fZQoaAZoCWgPQwgcmUf+YIhQwJSGlFKUaBVLUWgWR0BWN57b+Lm7dX2UKGgGaAloD0MINL+aAwTAV8CUhpRSlGgVS0xoFkdAVjlWzWwu/XV9lChoBmgJaA9DCLZnlgSoJFPAlIaUUpRoFUtvaBZHQFY55o4+8oR1fZQoaAZoCWgPQwhlAKjixnpSwJSGlFKUaBVLP2gWR0BWOfJ3gUDddX2UKGgGaAloD0MI/mSMD7NyUsCUhpRSlGgVS2JoFkdAVjr2zv7WNHV9lChoBmgJaA9DCEDZlCu8V1XAlIaUUpRoFUtIaBZHQFY7rq+rU9Z1fZQoaAZoCWgPQwi37BD/sGhRwJSGlFKUaBVLc2gWR0BWO/eDWbw0dX2UKGgGaAloD0MIAg6hSs1jWsCUhpRSlGgVS1hoFkdAVjzAzpHI63V9lChoBmgJaA9DCF9E2zF1IlbAlIaUUpRoFUtPaBZHQFY8maYu01J1fZQoaAZoCWgPQwhKC5dV2B5ZwJSGlFKUaBVLXmgWR0BWPRn8KohqdX2UKGgGaAloD0MId9fZkH8SQ8CUhpRSlGgVS0doFkdAVkAUKzAvc3V9lChoBmgJaA9DCOCfUiXKaWjAlIaUUpRoFUtnaBZHQFZAarWAf+11fZQoaAZoCWgPQwj7BFCMLM05wJSGlFKUaBVLSGgWR0BWRgckt29tdX2UKGgGaAloD0MIiUFg5dDEUsCUhpRSlGgVS0xoFkdAVklbiZOSGXV9lChoBmgJaA9DCJkMx/MZhErAlIaUUpRoFUs+aBZHQFZJEEC/47B1fZQoaAZoCWgPQwgYmYBfIyNAwJSGlFKUaBVLT2gWR0BWSkHIIWxhdX2UKGgGaAloD0MIFNBE2PDkHkCUhpRSlGgVS3hoFkdAVkr/DLr5ZnV9lChoBmgJaA9DCMi0No3t8FTAlIaUUpRoFUtHaBZHQFZMDe0ojOd1fZQoaAZoCWgPQwjH9lrQe3FcwJSGlFKUaBVLTWgWR0BWS/NZ/0/XdX2UKGgGaAloD0MI746M1eamVMCUhpRSlGgVS0loFkdAVkzXFtKqXHV9lChoBmgJaA9DCLlPjgJEAUDAlIaUUpRoFUtsaBZHQFZNgBcRlH11fZQoaAZoCWgPQwgAcVevIh1SwJSGlFKUaBVLS2gWR0BWThwZOzppdX2UKGgGaAloD0MIyxEykGeIXcCUhpRSlGgVS1loFkdAVk5G3F1jiHV9lChoBmgJaA9DCPCJdap8D1/AlIaUUpRoFUtJaBZHQFZOFPBSDRN1fZQoaAZoCWgPQwhZxLDDmK5QwJSGlFKUaBVLPGgWR0BWTrGBFuvVdX2UKGgGaAloD0MI5rD7juFXXMCUhpRSlGgVS2VoFkdAVlOXIEKVp3V9lChoBmgJaA9DCKlorP2dW0vAlIaUUpRoFUtJaBZHQFZW9GZuyeJ1fZQoaAZoCWgPQwj6KY4Dr/RBwJSGlFKUaBVLgmgWR0BWV/ICEHt4dX2UKGgGaAloD0MIVWmLa3yxUMCUhpRSlGgVS0JoFkdAVli5TZQHiXV9lChoBmgJaA9DCPmgZ7Pq6UnAlIaUUpRoFUtCaBZHQFZYbUPQOWl1fZQoaAZoCWgPQwiTisba315VwJSGlFKUaBVLamgWR0BWWNuYQarFdX2UKGgGaAloD0MIiL67lSVFVsCUhpRSlGgVSz9oFkdAVlpz90ihWnV9lChoBmgJaA9DCMSVs3dGVFLAlIaUUpRoFUtGaBZHQFZadPLxI8R1fZQoaAZoCWgPQwio4VtYN1BWwJSGlFKUaBVLSmgWR0BWW+dPLxI8dX2UKGgGaAloD0MIQUZAhSM7WsCUhpRSlGgVS1BoFkdAVl38UEgW8HV9lChoBmgJaA9DCFTgZBu4u1TAlIaUUpRoFUtRaBZHQFZgbjcVQAN1fZQoaAZoCWgPQwimQ6fn3aVRwJSGlFKUaBVLUmgWR0BWYJMURFqjdX2UKGgGaAloD0MImsx4W+lhVcCUhpRSlGgVS1doFkdAVmHNmlImPnV9lChoBmgJaA9DCGLZzCGphlbAlIaUUpRoFUtmaBZHQFZksHB1s+F1fZQoaAZoCWgPQwi+afrsgJM9wJSGlFKUaBVLYmgWR0BWZQF9roGIdX2UKGgGaAloD0MIFY+LahFZTsCUhpRSlGgVS01oFkdAVmVufmLcbnV9lChoBmgJaA9DCEG4Agr1bEfAlIaUUpRoFUt1aBZHQFZneYlY2bZ1fZQoaAZoCWgPQwjVdaimJN1GwJSGlFKUaBVLRmgWR0BWaFKXfIjodX2UKGgGaAloD0MIFw0Zj1LRMUCUhpRSlGgVS1FoFkdAVmmHpKSPl3V9lChoBmgJaA9DCJVGzOzzNmHAlIaUUpRoFUtYaBZHQFZsFZxJd0J1fZQoaAZoCWgPQwjp81FGXPpdwJSGlFKUaBVLWWgWR0BWbR2fTTfBdX2UKGgGaAloD0MIRS44g78bVMCUhpRSlGgVS15oFkdAVm/5aePJaXV9lChoBmgJaA9DCPLrh9hg3UPAlIaUUpRoFUtOaBZHQFZwFOfukUN1fZQoaAZoCWgPQwhi9x3DY+dbwJSGlFKUaBVLYWgWR0BWcK2KEWZadX2UKGgGaAloD0MI5e5zfLQWV8CUhpRSlGgVS0NoFkdAVnFFw1ivxHV9lChoBmgJaA9DCN9RY0LMwVXAlIaUUpRoFUtsaBZHQFZxh7mdRSB1fZQoaAZoCWgPQwhsJXSXxOlWwJSGlFKUaBVLS2gWR0BWcfL5hz/7dX2UKGgGaAloD0MIXFfMCG8nWMCUhpRSlGgVS3FoFkdAVnYyRB/qgXV9lChoBmgJaA9DCDBLOzWX9FTAlIaUUpRoFUtiaBZHQFZ3bqhUR4B1fZQoaAZoCWgPQwgwZHWr5xg2QJSGlFKUaBVLW2gWR0BWec/6fra/dX2UKGgGaAloD0MIV0EMdO25U8CUhpRSlGgVS1loFkdAVnoiILw4KnV9lChoBmgJaA9DCGLAkqtYmlPAlIaUUpRoFUtWaBZHQFZ7mukk8ih1ZS4="
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 28,
+    "_n_updates": 276,
     "n_steps": 1024,
     "gamma": 0.998,
     "gae_lambda": 0.98,

dqn-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a4523a4fac6fdc819df65cb1e6f81ff39f4b425e09d3905afe80ee831bd1d798
+oid sha256:a49e4861b8122108a2578f1b2cff9f5d0a97d5737d5e1c1bdcdaf4835a4b585c
 size 87865

dqn-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:49dd8ad9fec302f7a0a20391bc92ddcc67281fd6c0160ddfe02a357360b9568c
+oid sha256:f44c8d56557dd90c26d9fbb2c0b49808b59a3437df6571e3a079bd32958d1295
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": -64.42827943617013, "std_reward": 104.31319901295005, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-07T14:36:50.874121"}
+{"mean_reward": 262.5861671060246, "std_reward": 14.259336501656048, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-07T14:59:23.233664"}