Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -596.61 +/- 134.25
+      value: 247.72 +/- 41.99
       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 0x794f0f07a200>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x794f0f07a290>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x794f0f07a320>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x794f0f07a3b0>", "_build": "<function ActorCriticPolicy._build at 0x794f0f07a440>", "forward": "<function ActorCriticPolicy.forward at 0x794f0f07a4d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x794f0f07a560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x794f0f07a5f0>", "_predict": "<function ActorCriticPolicy._predict at 0x794f0f07a680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x794f0f07a710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x794f0f07a7a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x794f0f07a830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x794f0f00d840>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 106496, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1734661174182909523, "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": -0.0649599999999999, "_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": 130, "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": 512, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.005, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVrQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFowEZnVuY5SMDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu121", "GPU Enabled": "False", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "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 0x7bb13f69d870>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bb13f69d900>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bb13f69d990>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bb13f69da20>", "_build": "<function ActorCriticPolicy._build at 0x7bb13f69dab0>", "forward": "<function ActorCriticPolicy.forward at 0x7bb13f69db40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bb13f69dbd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bb13f69dc60>", "_predict": "<function ActorCriticPolicy._predict at 0x7bb13f69dcf0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bb13f69dd80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bb13f69de10>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bb13f69dea0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bb0e1fad480>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1734835493207713635, "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": 1840, "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": 512, "gamma": 0.99, "gae_lambda": 0.98, "ent_coef": 0.005, "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, "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 Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu121", "GPU Enabled": "False", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "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 sha256:67751cc2e370a43ea6daf6eef4c4e84fef5822edbe65917c39dd026afc586beb
-size 147438
+oid sha256:bee842b5ab7c39859f5cab8f13e21b6c1dd51f6b66db8aa33edf867e046c18c3
+size 147423

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 0x794f0f07a200>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x794f0f07a290>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x794f0f07a320>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x794f0f07a3b0>",
-        "_build": "<function ActorCriticPolicy._build at 0x794f0f07a440>",
-        "forward": "<function ActorCriticPolicy.forward at 0x794f0f07a4d0>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x794f0f07a560>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x794f0f07a5f0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x794f0f07a680>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x794f0f07a710>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x794f0f07a7a0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x794f0f07a830>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7bb13f69d870>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bb13f69d900>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bb13f69d990>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bb13f69da20>",
+        "_build": "<function ActorCriticPolicy._build at 0x7bb13f69dab0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7bb13f69db40>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bb13f69dbd0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bb13f69dc60>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7bb13f69dcf0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bb13f69dd80>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bb13f69de10>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bb13f69dea0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x794f0f00d840>"
+        "_abc_impl": "<_abc._abc_data object at 0x7bb0e1fad480>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 106496,
-    "_total_timesteps": 100000,
+    "num_timesteps": 1507328,
+    "_total_timesteps": 1500000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1734661174182909523,
+    "start_time": 1734835493207713635,
     "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": -0.0649599999999999,
+    "_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": 130,
+    "_n_updates": 1840,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",
@@ -79,7 +79,7 @@
     "n_envs": 16,
     "n_steps": 512,
     "gamma": 0.99,
-    "gae_lambda": 0.95,
+    "gae_lambda": 0.98,
     "ent_coef": 0.005,
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7f76511875b0b7ba60a137794914109dcbcc1b5cb6462b10eec3c05118c84981
+oid sha256:9a45e7c8526c052d465541afaba30eef7fc4893c83f898957dcb050225681798
 size 87978

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:143732c09394bef8ca3ca2afe7df7ed0f785e22863e80f94f960a42a14007917
+oid sha256:5f58dc94f36672ab66130fe8ecfa149fa9e7fb4d1d6842181bf468b9fe2eae0a
 size 43634

results.json

@@ -1 +1 @@
-{"mean_reward": -596.6124728247407, "std_reward": 134.25136143122833, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-12-20T02:22:16.532321"}
+{"mean_reward": 247.71935007350095, "std_reward": 41.99229293825897, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-12-22T03:12:22.637379"}