version2

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 231.39 +/- 75.79
+      value: 276.61 +/- 19.49
       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 0x7ded40777c70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ded40777d00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ded40777d90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ded40777e20>", "_build": "<function ActorCriticPolicy._build at 0x7ded40777eb0>", "forward": "<function ActorCriticPolicy.forward at 0x7ded40777f40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ded4078c040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ded4078c0d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ded4078c160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ded4078c1f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ded4078c280>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ded4078c310>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ded40788640>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1703541551225292613, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAGZAUr1c32u63Yimu8HzjDypKwo8Fsh0vQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3908, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
+{"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 0x7e97010e81f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e97010e8280>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e97010e8310>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e97010e83a0>", "_build": "<function ActorCriticPolicy._build at 0x7e97010e8430>", "forward": "<function ActorCriticPolicy.forward at 0x7e97010e84c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e97010e8550>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e97010e85e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7e97010e8670>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e97010e8700>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e97010e8790>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e97010e8820>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e9701082e40>"}, "verbose": 0, "policy_kwargs": {"net_arch": [64, 64]}, "num_timesteps": 5013504, "_total_timesteps": 5000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1703588646119339932, "learning_rate": 0.0003, "tensorboard_log": null, "_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": -0.0027007999999999477, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1530, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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": 5, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9393a2018fd430c6d3998c37f46fd44bb661b86723b51e462df54cda07f2987c
-size 147636
+oid sha256:434808d9d1591cec8af1f39bbe078636b122d9c2a2513a8b3e4e4cb901a54801
+size 148010

ppo-LunarLander-v2/data

@@ -4,54 +4,59 @@
         ":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 0x7ded40777c70>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ded40777d00>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ded40777d90>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ded40777e20>",
-        "_build": "<function ActorCriticPolicy._build at 0x7ded40777eb0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7ded40777f40>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ded4078c040>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ded4078c0d0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7ded4078c160>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ded4078c1f0>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ded4078c280>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ded4078c310>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7e97010e81f0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e97010e8280>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e97010e8310>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e97010e83a0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7e97010e8430>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7e97010e84c0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e97010e8550>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e97010e85e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7e97010e8670>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e97010e8700>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e97010e8790>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e97010e8820>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7ded40788640>"
+        "_abc_impl": "<_abc._abc_data object at 0x7e9701082e40>"
     },
-    "verbose": 1,
-    "policy_kwargs": {},
-    "num_timesteps": 1000448,
-    "_total_timesteps": 1000000,
+    "verbose": 0,
+    "policy_kwargs": {
+        "net_arch": [
+            64,
+            64
+        ]
+    },
+    "num_timesteps": 5013504,
+    "_total_timesteps": 5000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1703541551225292613,
+    "start_time": 1703588646119339932,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAGZAUr1c32u63Yimu8HzjDypKwo8Fsh0vQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
     },
     "_last_original_obs": null,
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.00044800000000000395,
+    "_current_progress_remaining": -0.0027007999999999477,
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "gAWV4QsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHGcOtnwob6MAWyUS9yMAXSUR0CxhIqKcd5qdX2UKGgGR0Bx8UCCBf8eaAdL22gIR0CxhJUh7mdRdX2UKGgGR0By2NOGj9GaaAdL5mgIR0CxhLFJlJ6IdX2UKGgGR0Bu9/y5I6KcaAdLy2gIR0CxhLLt7a7FdX2UKGgGR0Bv0JE+gUUPaAdL1WgIR0CxhLmNWEK3dX2UKGgGR0BxB+eYlY2baAdL4WgIR0CxhLim2sq8dX2UKGgGR0BzMmdXko4NaAdLyGgIR0CxhN7wKBuodX2UKGgGR0BwhIc2itaIaAdLxmgIR0CxhOYvvjOtdX2UKGgGR0Bx/0GLUCq7aAdL1mgIR0CxhOlJcxCZdX2UKGgGR0Bu+KCcwxnGaAdLyWgIR0CxhRgwblzVdX2UKGgGR0Byqxqj8DSxaAdL62gIR0CxhS6UFB6bdX2UKGgGR0BxWVUDMeOoaAdL72gIR0CxhUKESM99dX2UKGgGR0BzRzKQq7ROaAdLy2gIR0CxhUUug6EKdX2UKGgGR0BxAjLNfPX1aAdLx2gIR0CxhUgN0/4ZdX2UKGgGR0By/o3Lmp2maAdLz2gIR0CxhWcl5WzXdX2UKGgGR0Bxp4Y3vQWvaAdL5GgIR0CxhYbD63y7dX2UKGgGR0BxmyV4X40uaAdL5WgIR0CxhbLQgLZ0dX2UKGgGR0Bx/TpFCswMaAdLxmgIR0CxhbeuFHrhdX2UKGgGR0Bz49baAWi2aAdLzWgIR0CxhbrEDQqqdX2UKGgGR0Bxz6L2pQ1raAdL5GgIR0Cxhbua4MF2dX2UKGgGR0BxtyV2Rq46aAdLsWgIR0CxhcPU4JeFdX2UKGgGR0Bzgz127nPnaAdL4GgIR0CxixLWVeKLdX2UKGgGR0BwPHD0lJHzaAdLx2gIR0CxiyDP4VRDdX2UKGgGR0Bza9xo7FKkaAdNAAFoCEdAsYs0Lc9GJHV9lChoBkdAcs35nDiwS2gHS91oCEdAsYs/ZCfHxXV9lChoBkdAcIaZE2HclGgHS9BoCEdAsYtg2ETQFHV9lChoBkdAcXuu3trsSmgHS6toCEdAsYthFYuCgHV9lChoBkdAc08+NLlFMWgHS8loCEdAsYtuumrKeXV9lChoBkdAcahFJg9eQmgHS89oCEdAsYuKSU1Q7HV9lChoBkdAcwaHh0hePmgHS+VoCEdAsYuq/zreInV9lChoBkdAcWe3c580DWgHS7ZoCEdAsYuwb0e2eHV9lChoBkdAc3AjlxOtXGgHS+hoCEdAsYvVRNyo43V9lChoBkdAcaMdZq20A2gHS8NoCEdAsYvuVRk3CXV9lChoBkdAcrwDyvs7dWgHS75oCEdAsYvwDOkcj3V9lChoBkdAcnaC8e0XxmgHS8NoCEdAsYvzvH93r3V9lChoBkdAchSuPFNtZWgHS+JoCEdAsYwgC0WuYHV9lChoBkdAcOZQkX1rZmgHS91oCEdAsYwjQw9JSXV9lChoBkdAclemOU+s5mgHS7RoCEdAsYwlXGOuJXV9lChoBkdAcuRR2bG3nmgHS9toCEdAsYw06GQCCHV9lChoBkdAcwDkGA08/2gHS9poCEdAsYxCAUcn3XV9lChoBkdAcHJ0U47zTWgHS7xoCEdAsYxasRxtHnV9lChoBkdAc/465Xlr/WgHS95oCEdAsYxlMrVe8nV9lChoBkdAcz0XFLnLaGgHS9RoCEdAsYx52+wkgXV9lChoBkdAcYziV0Lc9GgHS8NoCEdAsYyNefI0ZXV9lChoBkdAcWRxZuAI6mgHS95oCEdAsYyXSVnmJXV9lChoBkdAcuiCAc1fmmgHS9NoCEdAsYzDyhBZ6nV9lChoBkdAcuZ1dgOSXGgHS9poCEdAsYzStCAtnXV9lChoBkdAcS83o9s7+2gHS8FoCEdAsYzV8b70nXV9lChoBkdAb2oD3/Pw/mgHS7doCEdAsYzixW1c+3V9lChoBkdAcyEbJOnEVGgHS8poCEdAsYz/iJfplnV9lChoBkdAcclwYcebNWgHS7doCEdAsY0jyDqW1XV9lChoBkdAUoyWu5jH42gHS4doCEdAsY0qJZW7v3V9lChoBkdAcflObiIcimgHS7doCEdAsY089s7+1nV9lChoBkdAbbxeMyad+WgHS7poCEdAsY1VgAp8W3V9lChoBkdAc+u29cry2GgHS/hoCEdAsY1U9eQdS3V9lChoBkdAcDtDRMN+b2gHS9VoCEdAsY1bDCP6sXV9lChoBkdAdBeDQJHAh2gHS95oCEdAsY1mjynUD3V9lChoBkdAcMqYBNmDlGgHS6poCEdAsY2tqDbrT3V9lChoBkdAcOAgxJul42gHS9doCEdAsY2vaJyhjHV9lChoBkdAdLO9ECvHLmgHS7loCEdAsY2/B55Z83V9lChoBkdAc3iX9itq6GgHS+loCEdAsY38PXkHU3V9lChoBkdAb+VN+LFXJmgHS7ZoCEdAsY4B09yLh3V9lChoBkdAcdwP3SKFZmgHS81oCEdAsY5SxX4j8nV9lChoBkdAcjwnv2GqP2gHS+hoCEdAsY5v9bX6InV9lChoBkdAc5C5VOsT4GgHS+toCEdAsY57MUypJnV9lChoBkdAb+4SJ0nw5WgHS9hoCEdAsY6RrTH80nV9lChoBkdAcIvw2l2vCGgHS8hoCEdAsY6Vd9lVcXV9lChoBkdAcmi0elsP8WgHS7xoCEdAsY6W938n/nV9lChoBkdAcEQxZuAI6mgHS7VoCEdAsY6nCrLhaXV9lChoBkdAcURqtHQQc2gHS7RoCEdAsY6xhTfixXV9lChoBkdAcvOf/WDpT2gHS79oCEdAsY6ztVrAQHV9lChoBkdAcw84KQaJh2gHS9loCEdAsY65jkMkQnV9lChoBkdAckVlmvnr6mgHS8xoCEdAsY7HAxi5NHV9lChoBkdAc7ZOG0u14WgHS8JoCEdAsY8HrE9+w3V9lChoBkdAcwvwbVBlc2gHS8ZoCEdAsY8e/336AXV9lChoBkdAcUEOryUcGWgHS9ZoCEdAsY8qUyHmBHV9lChoBkdAcd6fG+9Jz2gHS61oCEdAsY8sQCjk/HV9lChoBkdAcD8N0NjLCGgHS8VoCEdAsY9W4I8hcXV9lChoBkdAUl41WKdhAmgHS4xoCEdAsY+fleWv83V9lChoBkdAb+9tXPqs2mgHS79oCEdAsY+hAlfJFXV9lChoBkdAcg/HpKSPl2gHS8RoCEdAsY/LOE/SpnV9lChoBkdAb4kOyVv/BGgHS8VoCEdAsY/ZAbADaHV9lChoBkdAcgJfxMFlkGgHS8FoCEdAsY/nwF1SwXV9lChoBkdAcchPGQ0XQGgHS8NoCEdAsY/xi4J/onV9lChoBkdAcxxv24/eL2gHS9RoCEdAsZAg7Njbz3V9lChoBkdAcxNhPCVKPGgHS8loCEdAsZAga/ATI3V9lChoBkdAcvB6iCaqj2gHS89oCEdAsZAzI1cdHXV9lChoBkdAc7W4smOU+2gHS+9oCEdAsZA3dtVJc3V9lChoBkdAcUeNnoPkJmgHS+xoCEdAsZBFVBD5TXV9lChoBkdAUW24b0e2eGgHS5FoCEdAsZBSJAMUh3V9lChoBkdAcq/AMUh3aGgHS85oCEdAsZBgJfICEHV9lChoBkdAb8y1w5vLo2gHS8VoCEdAsZBlpqREGHV9lChoBkdAcgv2CNCJGmgHS81oCEdAsZB5k3CKrXV9lChoBkdAcVUcHGCI12gHS9hoCEdAsZCFSqEOAnV9lChoBkdAcCCFUADJVGgHS7toCEdAsZC0Bkqc3HV9lChoBkdAcnQs3Q2MsGgHS7doCEdAsZDVmNBF/nV9lChoBkdAcdRFQVKwp2gHS9ZoCEdAsZDbKEFnqXV9lChoBkdAcOU0Sh8IA2gHS7ZoCEdAsZDen5zo2XV9lChoBkdAcx5IqslsxmgHS9toCEdAsZD/PZ7HAHV9lChoBkdAdAVFpfx+a2gHS9JoCEdAsZEL0Zm7KHVlLg=="
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 3908,
+    "_n_updates": 1530,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",
@@ -69,14 +74,14 @@
     },
     "action_space": {
         ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
-        ":serialized:": "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",
+        ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
         "n": "4",
         "start": "0",
         "_shape": [],
         "dtype": "int64",
-        "_np_random": "Generator(PCG64)"
+        "_np_random": null
     },
-    "n_envs": 1,
+    "n_envs": 16,
     "n_steps": 1024,
     "gamma": 0.999,
     "gae_lambda": 0.98,
@@ -84,7 +89,7 @@
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,
     "batch_size": 64,
-    "n_epochs": 4,
+    "n_epochs": 5,
     "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 sha256:8de9354da80e17d4ee3bd2b49eef772be67522f307537c575c9b94901eb35b8e
+oid sha256:0eb7f9af1dee1d0440256a3e2f4ab64fc37d08828bb7d85ac634ec88e1de6929
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:67cc9062c8cc457d8f7d1014880772b6b075536585415b3bb166a1713d8a105d
+oid sha256:f8bc25f2c731018c244aab7f65b87dc52b66f677fc8262a325a3cf941279fb2b
 size 43762

results.json

@@ -1 +1 @@
-{"mean_reward": 231.3873787, "std_reward": 75.78514625178978, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-12-25T22:34:57.173135"}
+{"mean_reward": 276.6080709, "std_reward": 19.488516808454857, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-12-26T12:23:03.733682"}