Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 270.23 +/- 25.25
+      value: -103.62 +/- 22.53
       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 0x79c5653689d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79c565368a60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79c565368af0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79c565368b80>", "_build": "<function ActorCriticPolicy._build at 0x79c565368c10>", "forward": "<function ActorCriticPolicy.forward at 0x79c565368ca0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79c565368d30>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79c565368dc0>", "_predict": "<function ActorCriticPolicy._predict at 0x79c565368e50>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79c565368ee0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79c565368f70>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79c565369000>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79c565308cc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718086169142384286, "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": -0.015808000000000044, "_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": 248, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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": 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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "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 0x7a600c79c4c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a600c79c550>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a600c79c5e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a600c79c670>", "_build": "<function ActorCriticPolicy._build at 0x7a600c79c700>", "forward": "<function ActorCriticPolicy.forward at 0x7a600c79c790>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a600c79c820>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a600c79c8b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7a600c79c940>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a600c79c9d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a600c79ca60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a600c79caf0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a600c7a03c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718171686614293801, "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": -0.004885333333333408, "_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": 736, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.9, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 8, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "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 sha256:3d7f4ced94a5fd5678a2851e957381910a3c266b619d83c5d5f9ad14a7cfd1ca
-size 148044
+oid sha256:9f5e191846bfa24844781ebd166eb3d28f3beb1e79a7ff6538cc2ca710566638
+size 148087

ppo-LunarLander-v2/data

@@ -4,34 +4,34 @@
         ":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 0x79c5653689d0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79c565368a60>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79c565368af0>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79c565368b80>",
-        "_build": "<function ActorCriticPolicy._build at 0x79c565368c10>",
-        "forward": "<function ActorCriticPolicy.forward at 0x79c565368ca0>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x79c565368d30>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79c565368dc0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x79c565368e50>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79c565368ee0>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79c565368f70>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x79c565369000>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7a600c79c4c0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a600c79c550>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a600c79c5e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a600c79c670>",
+        "_build": "<function ActorCriticPolicy._build at 0x7a600c79c700>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7a600c79c790>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a600c79c820>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a600c79c8b0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7a600c79c940>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a600c79c9d0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a600c79ca60>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a600c79caf0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x79c565308cc0>"
+        "_abc_impl": "<_abc._abc_data object at 0x7a600c7a03c0>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 1507328,
+    "_total_timesteps": 1500000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1718086169142384286,
+    "start_time": 1718171686614293801,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -41,17 +41,17 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.015808000000000044,
+    "_current_progress_remaining": -0.004885333333333408,
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 248,
+    "_n_updates": 736,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
@@ -78,13 +78,13 @@
     },
     "n_envs": 16,
     "n_steps": 1024,
-    "gamma": 0.999,
+    "gamma": 0.9,
     "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": 8,
     "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:ee947b093606d66be2453c2a5e2270ce7382daca60eca7f04ae3bc0e29506cb5
+oid sha256:6e1383f926243d5a6410745fcd420a843028a80a4838c5640fdbebf82b6c9c7b
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:dc835e664173e9fba79e28b7b8e03764b16ed976e15e1ad5b885f26693d59b6e
+oid sha256:a734f3187ee3a2c706a873238f2eb83fd6731855d020da1efc518be9bb0fe730
 size 43762

results.json

@@ -1 +1 @@
-{"mean_reward": 270.23160906206465, "std_reward": 25.254117612716048, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-11T06:39:38.166906"}
+{"mean_reward": -103.6193093459573, "std_reward": 22.533689691320593, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-12T06:40:46.471463"}