Create model card

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 145.63 +/- 91.47
+      value: 266.77 +/- 23.58
       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 0x7f15829f4290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f15829f4320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f15829f43b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f15829f4440>", "_build": "<function ActorCriticPolicy._build at 0x7f15829f44d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f15829f4560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f15829f45f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f15829f4680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f15829f4710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f15829f47a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f15829f4830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f1582a38810>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651731173.9040565, "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": 124, "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 0x7f15829f4290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f15829f4320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f15829f43b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f15829f4440>", "_build": "<function ActorCriticPolicy._build at 0x7f15829f44d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f15829f4560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f15829f45f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f15829f4680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f15829f4710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f15829f47a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f15829f4830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f1582a38810>"}, "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": 1651732527.3520007, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "_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": 620, "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": 128, "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-5.4.188+-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-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:020fe859f3d8533fbba8d8b84b164a92a53776863078d5a889f73b1ec937a7fe
-size 144020
+oid sha256:9770a5f6d1eac153854ed229de92252efeca05018041e3adf6e93421613b84bc
+size 144080

ppo-LunarLander-v2/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 507904,
-    "_total_timesteps": 500000,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1651731173.9040565,
+    "start_time": 1651732527.3520007,
     "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'>",
@@ -69,21 +69,21 @@
     "_current_progress_remaining": -0.015808000000000044,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "gAWVbBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIueF30y2bCsCUhpRSlIwBbJRL0owBdJRHQIpQq9sabWp1fZQoaAZoCWgPQwgdr0D0pNNVQJSGlFKUaBVN6ANoFkdAilL+m3vx6XV9lChoBmgJaA9DCBrEB3b8czJAlIaUUpRoFUutaBZHQIpg2AoXsPd1fZQoaAZoCWgPQwiqK5/leUBYQJSGlFKUaBVN6ANoFkdAinaeiSJTEXV9lChoBmgJaA9DCKd0sP7P/T3AlIaUUpRoFU1tAWgWR0CKfxDej2zwdX2UKGgGaAloD0MIzbBR1m83VECUhpRSlGgVTegDaBZHQIqEcjcEeQx1fZQoaAZoCWgPQwgzwAXZsv9bQJSGlFKUaBVN6ANoFkdAiohdPLxI8XV9lChoBmgJaA9DCHgLJCh+ImFAlIaUUpRoFU3oA2gWR0CKs1xx1gYxdX2UKGgGaAloD0MIVHB4QUQqY0CUhpRSlGgVTegDaBZHQIq0xf2K2rp1fZQoaAZoCWgPQwhEwYwp2DBhQJSGlFKUaBVN6ANoFkdAirfVPWQOnXV9lChoBmgJaA9DCEuuYvGbT11AlIaUUpRoFU3oA2gWR0CKusuV5a/zdX2UKGgGaAloD0MIMBFvnf8cYkCUhpRSlGgVTegDaBZHQIrJH2Xb/Ot1fZQoaAZoCWgPQwiNQpJZvYP+P5SGlFKUaBVLz2gWR0CK2Pi6xxDLdX2UKGgGaAloD0MIZk8Cm3NPX0CUhpRSlGgVTegDaBZHQIsif8baRIV1fZQoaAZoCWgPQwiZ2ecxytdfQJSGlFKUaBVN6ANoFkdAiypSjYZl4HV9lChoBmgJaA9DCGHEPgEUaV1AlIaUUpRoFU3oA2gWR0CLNGN4JNTMdX2UKGgGaAloD0MIVp3VAnuVXUCUhpRSlGgVTegDaBZHQIs0dAeJYT11fZQoaAZoCWgPQwjs98Q6Vc9QQJSGlFKUaBVN6ANoFkdAizolb/wRXnV9lChoBmgJaA9DCK62Yn/ZCmVAlIaUUpRoFU3oA2gWR0CLPI9eyAx0dX2UKGgGaAloD0MIh272B8ryXECUhpRSlGgVTegDaBZHQItLlndweeZ1fZQoaAZoCWgPQwhZ+zvbo5cYwJSGlFKUaBVL02gWR0CLU7YJVsDXdX2UKGgGaAloD0MINuZ1xCFrJcCUhpRSlGgVTY4BaBZHQItXu3lS0jV1fZQoaAZoCWgPQwjeHoSAfH5dQJSGlFKUaBVN6ANoFkdAi2Ewd0aIe3V9lChoBmgJaA9DCIhnCTICJ1pAlIaUUpRoFU3oA2gWR0CLaRhOxjaxdX2UKGgGaAloD0MIgczOonfSP0CUhpRSlGgVS7doFkdAi2lB0hePaXV9lChoBmgJaA9DCPsgy4KJPFlAlIaUUpRoFU3oA2gWR0CLbgztTkyUdX2UKGgGaAloD0MIT0ATYUPxYkCUhpRSlGgVTegDaBZHQItxo0IkZ751fZQoaAZoCWgPQwj52ch1U7I2QJSGlFKUaBVNFQFoFkdAi3+wqAjIJnV9lChoBmgJaA9DCC+ISE27wC9AlIaUUpRoFU1SAWgWR0CLjP5NXYDldX2UKGgGaAloD0MI2C0CY/30YkCUhpRSlGgVTegDaBZHQIuVEb5uZTh1fZQoaAZoCWgPQwh6G5sdqZZhQJSGlFKUaBVN6ANoFkdAi5i7bUPQOXV9lChoBmgJaA9DCC2T4Xg+LVpAlIaUUpRoFU3oA2gWR0CLm1+qioKldX2UKGgGaAloD0MIx3+BIMBVZECUhpRSlGgVTegDaBZHQIunnykKu0V1fZQoaAZoCWgPQwiZuiu74JhhQJSGlFKUaBVN6ANoFkdAi/9X1anrIHV9lChoBmgJaA9DCFyRmKCGsFxAlIaUUpRoFU3oA2gWR0CMB0Rs/IKddX2UKGgGaAloD0MIMGe2K/TpO8CUhpRSlGgVS99oFkdAjAvc1n/T9nV9lChoBmgJaA9DCH6qCg3EAF9AlIaUUpRoFU3oA2gWR0CMENHT7VJ+dX2UKGgGaAloD0MIt0QuOINIYUCUhpRSlGgVTegDaBZHQIwWQ2dd3St1fZQoaAZoCWgPQwg08+SaAsdZQJSGlFKUaBVN6ANoFkdAjBir/Khcq3V9lChoBmgJaA9DCMe7I2O1AThAlIaUUpRoFUuoaBZHQIwj9sBQvYh1fZQoaAZoCWgPQwhwQbYsXxVKQJSGlFKUaBVN6ANoFkdAjDysFdLQHHV9lChoBmgJaA9DCCLBVDNr5l1AlIaUUpRoFU3oA2gWR0CMRGCV8kUsdX2UKGgGaAloD0MI2zAKgkdRYUCUhpRSlGgVTegDaBZHQIxEiup0fYB1fZQoaAZoCWgPQwhpyeNp+VtJwJSGlFKUaBVL3mgWR0CMRw4+bExZdX2UKGgGaAloD0MIjgWFQZlVYUCUhpRSlGgVTegDaBZHQIxIw04zabp1fZQoaAZoCWgPQwjlQXqKnGxkQJSGlFKUaBVN6ANoFkdAjEvTWwu/UXV9lChoBmgJaA9DCCcz3lZ621pAlIaUUpRoFU3oA2gWR0CMWImVqveQdX2UKGgGaAloD0MIf9qoTgeyCECUhpRSlGgVS9doFkdAjGS2cz67/XV9lChoBmgJaA9DCHsuU5NgZmNAlIaUUpRoFU3oA2gWR0CMZNijtXxOdX2UKGgGaAloD0MI2VpfJLSdQECUhpRSlGgVS+ZoFkdAjGizw+dK/XV9lChoBmgJaA9DCKj/rPnxbUVAlIaUUpRoFU3oA2gWR0CMbCNWluWKdX2UKGgGaAloD0MIv+/fvDhyYECUhpRSlGgVTegDaBZHQIxvZvYODrZ1fZQoaAZoCWgPQwjQ8dHijDRYQJSGlFKUaBVN6ANoFkdAjHG1XvH933V9lChoBmgJaA9DCAbYR6eu/PI/lIaUUpRoFUvSaBZHQIx2GIMz/Id1fZQoaAZoCWgPQwgIOe//4/A0wJSGlFKUaBVLymgWR0CMkGM2m52AdX2UKGgGaAloD0MILxUb8zqsYUCUhpRSlGgVTegDaBZHQIyVBm7J4jd1fZQoaAZoCWgPQwhgyOpWz6pUQJSGlFKUaBVN6ANoFkdAjN2TmOlwcnV9lChoBmgJaA9DCH7gKk+guGBAlIaUUpRoFU3oA2gWR0CM5/pudf9hdX2UKGgGaAloD0MIy4EeatsHX0CUhpRSlGgVTegDaBZHQIzuDkdV/+d1fZQoaAZoCWgPQwhma32R0KY5QJSGlFKUaBVLtGgWR0CM72uFHrhSdX2UKGgGaAloD0MIrVCk+7nPY0CUhpRSlGgVTegDaBZHQIzwtpj+aSd1fZQoaAZoCWgPQwgeU3dlFwhCQJSGlFKUaBVLuGgWR0CM9BYUWVNYdX2UKGgGaAloD0MIWRR2UfSAAcCUhpRSlGgVS+9oFkdAjRUk6DGtIXV9lChoBmgJaA9DCBu+hXVjv2FAlIaUUpRoFU3oA2gWR0CNFp4mCyyEdX2UKGgGaAloD0MIscHCSZqzXECUhpRSlGgVTegDaBZHQI0evIS13MZ1fZQoaAZoCWgPQwjUfJV8bNBiQJSGlFKUaBVN6ANoFkdAjR7mMn7YTXV9lChoBmgJaA9DCIQR+wRQP15AlIaUUpRoFU3oA2gWR0CNJy42jwhGdX2UKGgGaAloD0MIn1voSgTPW0CUhpRSlGgVTegDaBZHQI1FfMbFS891fZQoaAZoCWgPQwi14hsKn3lQQJSGlFKUaBVN6ANoFkdAjUWnVf/m1nV9lChoBmgJaA9DCFZ/hGHAWixAlIaUUpRoFUvyaBZHQI1HA593KSx1fZQoaAZoCWgPQwje5o2TwnQvwJSGlFKUaBVLyWgWR0CNSMxrSE13dX2UKGgGaAloD0MIb4RFRZxYXUCUhpRSlGgVTegDaBZHQI1JvyiEg4h1fZQoaAZoCWgPQwgEBHP0+LpiQJSGlFKUaBVN6ANoFkdAjU0dIGyHEnV9lChoBmgJaA9DCJV9VwT/6yzAlIaUUpRoFU1YAWgWR0CNTulBQemvdX2UKGgGaAloD0MICTICKpx4YUCUhpRSlGgVTegDaBZHQI1QNdHDrJN1fZQoaAZoCWgPQwjT2jS2145gQJSGlFKUaBVN6ANoFkdAjVbkJBw++3V9lChoBmgJaA9DCPW7sDVbhTNAlIaUUpRoFUvTaBZHQI1iWV1Oj7B1fZQoaAZoCWgPQwham8b2Wsg2wJSGlFKUaBVL2mgWR0CNZhzr/sE8dX2UKGgGaAloD0MI1ZRkHY7OD8CUhpRSlGgVTSsBaBZHQI1zMLfDUEx1fZQoaAZoCWgPQwh7vfvjPUlrQJSGlFKUaBVNJQFoFkdAjbksLWqcVnV9lChoBmgJaA9DCN5Wem22ymFAlIaUUpRoFU3oA2gWR0CNuo/zJ6ppdX2UKGgGaAloD0MILEoJwapzXkCUhpRSlGgVTegDaBZHQI3DxQHiWE91fZQoaAZoCWgPQwhZNnNI6qZgQJSGlFKUaBVN6ANoFkdAjckd2ovSMXV9lChoBmgJaA9DCFN1j2yu7VdAlIaUUpRoFU3oA2gWR0CNy3cTJyQxdX2UKGgGaAloD0MIaThlbr57YECUhpRSlGgVTegDaBZHQI3OmP3i7051fZQoaAZoCWgPQwijA5Kwb7BWQJSGlFKUaBVN6ANoFkdAje56cAimmHV9lChoBmgJaA9DCJNuS+QC+mNAlIaUUpRoFU3oA2gWR0CN99Enb7CSdX2UKGgGaAloD0MIrgyqDU7cJkCUhpRSlGgVTVEBaBZHQI39RWYF7ld1fZQoaAZoCWgPQwiJYYcx6Y8WwJSGlFKUaBVLw2gWR0COIN+glF+edX2UKGgGaAloD0MIyLJg4o+qUkCUhpRSlGgVTegDaBZHQI4hqF23azx1fZQoaAZoCWgPQwhf7SjOUVJgQJSGlFKUaBVN6ANoFkdAjiNBt+CsfnV9lChoBmgJaA9DCE7TZwfcqGFAlIaUUpRoFU3oA2gWR0COKpE87p3YdX2UKGgGaAloD0MIPfGcLaC2Y0CUhpRSlGgVTegDaBZHQI4ujx3FDOV1fZQoaAZoCWgPQwi+vtalRsNcQJSGlFKUaBVN6ANoFkdAjja6x5cC5nV9lChoBmgJaA9DCP6cgvxsYGNAlIaUUpRoFU3oA2gWR0COQ9fiPyTZdX2UKGgGaAloD0MI+13Ymq08FMCUhpRSlGgVS+poFkdAjkc+yzHCGnV9lChoBmgJaA9DCNyeILHdq1dAlIaUUpRoFU3oA2gWR0COR/hRZU1idX2UKGgGaAloD0MIkZighm+/YUCUhpRSlGgVTegDaBZHQI5UDHIZIhB1fZQoaAZoCWgPQwgCgc6kzTdgQJSGlFKUaBVN6ANoFkdAjlhuK4x1xXV9lChoBmgJaA9DCKKXUSw3dWFAlIaUUpRoFU3oA2gWR0COWcNx2jfvdWUu"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 124,
+    "_n_updates": 620,
     "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,
+    "batch_size": 128,
+    "n_epochs": 10,
     "clip_range": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6d0c2588fd93a7267ba1d9f4ba3314e695f5d400bf450763e9c134ba15255288
-size 84829
+oid sha256:ef349b7fccae3f800d07da4967e2f93a4abe926d7b3b60c05b07256a7f9c5091
+size 84893

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:907db5dbae57d64f9dafe0fd6231d18dc86b2ee0e6e2fef0b4412b20be7c821a
+oid sha256:5b7172ac7771133fdb0a55f88d3b808798aeca86df5186f82364b4d5d370a43b
 size 43201

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a9e89f5a22ea685079a4599ae44e1407d4f08c8196c0a5c1e2ae9c3c56e084fe
-size 195383
+oid sha256:f6325a273f44aeeb98caaa11e3f6d5caf61067ddc6046b580dfd6df090fb187f
+size 202822

results.json

@@ -1 +1 @@
-{"mean_reward": 145.63288796181715, "std_reward": 91.46849903861047, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-05T06:30:48.962943"}
+{"mean_reward": 266.76922482655846, "std_reward": 23.582158932281136, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-05T07:15:50.652637"}