Upload PPO LunarLander-v2 trained agent

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 258.00 +/- 22.62
+      value: 237.58 +/- 69.12
       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 0x7aff458ca0e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7aff458ca170>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7aff458ca200>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7aff458ca290>", "_build": "<function ActorCriticPolicy._build at 0x7aff458ca320>", "forward": "<function ActorCriticPolicy.forward at 0x7aff458ca3b0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7aff458ca440>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7aff458ca4d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7aff458ca560>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7aff458ca5f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7aff458ca680>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7aff458ca710>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7aff63e58280>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1719979071723113730, "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:": "gAWVOQwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHCQ3SBshxKMAWyUTSEBjAF0lEdAld5W9xp+MXV9lChoBkdAb+hPepGWlmgHTVsBaAhHQJXfiObRWtF1fZQoaAZHQHJsFBdD6WRoB00sAWgIR0CV4KzImw7ldX2UKGgGR0BxIdkYoAn2aAdNCgFoCEdAleDGB8QZoHV9lChoBkdAcIQLDAJswmgHTScBaAhHQJXioPDpC8h1fZQoaAZHQHAAcOXmeUZoB00AAWgIR0CV47OARTS9dX2UKGgGR0BuG0G5c1O1aAdNAwFoCEdAleO+lbeMynV9lChoBkdAcqcpt78ejmgHTUcBaAhHQJXkULy+YdB1fZQoaAZHQHJ4Kdc0LtxoB00iAWgIR0CV5GTTvy9VdX2UKGgGR0Bwf4x7AtWdaAdNwAFoCEdAleWVpXZGrnV9lChoBkdAcR4sDGLk0mgHTZIBaAhHQJXmK2rn1Wd1fZQoaAZHQHKq9RaX8fpoB00zAWgIR0CV5pTrmhdudX2UKGgGR0Bv1HfhuO0caAdNDQFoCEdAlebgBLf1pXV9lChoBkdAb2x4zJp35mgHTSIBaAhHQJXnaNHYpUh1fZQoaAZHQHCxm1lXiitoB02XAWgIR0CV6evo/zJ7dX2UKGgGR0BxLjXumaYvaAdNZAFoCEdAlepEtAcDKnV9lChoBkdAcK8iiZfD12gHTT4BaAhHQJXqZjCpFTh1fZQoaAZHQHEPV3IMjNZoB018AWgIR0CV6tEmICU5dX2UKGgGR0BwVTzXjENwaAdL8GgIR0CV6xkWRA8kdX2UKGgGR0Bt6FfeDWbxaAdNBwFoCEdAlezLncL0BnV9lChoBkdAcwJh60IC2mgHTW0BaAhHQJXtLbfxc3V1fZQoaAZHQHD9AYxcmjVoB02KAWgIR0CV7kWhysCDdX2UKGgGR0Bwq7ulXRw7aAdNOgFoCEdAle6dH2AXmHV9lChoBkdAcM/9ovi97GgHTQUBaAhHQJXuqotL+P11fZQoaAZHQG5/lN+LFXJoB00qAWgIR0CV7sY9gWrPdX2UKGgGR0BwKOy+pOvdaAdNMwFoCEdAle71nRLK3nV9lChoBkdAbHZg4Otnw2gHTQ8BaAhHQJXwHSSeRPp1fZQoaAZHQG6KqVQhwERoB00WAWgIR0CV8L5ckdFOdX2UKGgGR0ByptaSs8xLaAdNSgFoCEdAlfIc4T9KmXV9lChoBkdAcE90gKWszWgHTTUBaAhHQJXywFfReC11fZQoaAZHQHIskTDfm9xoB00QAWgIR0CV9CTzND+jdX2UKGgGR0BxDsdn003waAdNLAFoCEdAlfYjb349HXV9lChoBkdAcjc0fYBeX2gHTSYBaAhHQJX3PXVbzK91fZQoaAZHQHEMIvN/vv1oB01BAWgIR0CV96kv9LpSdX2UKGgGR0BxbOBwuM/AaAdL/2gIR0CV+Jllbu+idX2UKGgGR0BzDY9r433paAdNTwFoCEdAlfjs9fTkQ3V9lChoBkdAcAWahHskZGgHTRABaAhHQJX47OxB3Rp1fZQoaAZHQHHQWax5cC5oB00WAWgIR0CV/BJokAxSdX2UKGgGR0BuoY1UEPlNaAdNHwFoCEdAlfxwSBbwB3V9lChoBkdAccRr6ciGFmgHTSwBaAhHQJX9+uuA7Pp1fZQoaAZHQG2yxnFo+OhoB00VAWgIR0CV/lE8JUo8dX2UKGgGR0BuEbwYtQKsaAdNEQFoCEdAlf8JKjBVMnV9lChoBkdAcGZxFiKBNGgHTVcBaAhHQJYABJxvNvB1fZQoaAZHQG55AB91EE1oB02eAWgIR0CWA7Gd7OVxdX2UKGgGR0BxuqtYB/7SaAdL+2gIR0CWGRwYtQKsdX2UKGgGR0BxISVmjCYUaAdNXwFoCEdAlhnGi5/b03V9lChoBkdAcHPzbvgFYGgHTVcBaAhHQJYaBEF4cFR1fZQoaAZHQG9f0fHPu5VoB00/AWgIR0CWGkVhTfixdX2UKGgGR0BxLr8l5WzXaAdL+WgIR0CWGp2q1gIAdX2UKGgGR0BxterDIikgaAdNEAFoCEdAlhrAw482aXV9lChoBkdAcGhV0tAcDWgHTR0BaAhHQJYa7Kifxtp1fZQoaAZHQE0TSFXaJyhoB0vSaAhHQJYbcAlv60p1fZQoaAZHQHC3lkhA4XJoB00eAWgIR0CWG9Pz4DcNdX2UKGgGR0BxBaorFwT/aAdNNwFoCEdAlhyFVYISlHV9lChoBkdAcwCGgSOBD2gHTRkBaAhHQJYdpS3solV1fZQoaAZHQHIRriQ1aW5oB00qAWgIR0CWH3K3/givdX2UKGgGR0Bu2Fpyp71JaAdNOQFoCEdAlh+SgK4QSXV9lChoBkdAcMBZLZi/f2gHTUUBaAhHQJYfzMzMzM11fZQoaAZHQHJdsejmCAdoB01AAWgIR0CWIK5eZ5RkdX2UKGgGR0ByWEiHIp6QaAdNLwFoCEdAliJFBMSK33V9lChoBkdAcWCcQyylemgHTRYBaAhHQJYimGFi8Wd1fZQoaAZHQG/EdbX6InBoB00WAWgIR0CWItbi6xxDdX2UKGgGR0BuCZ5cC5mRaAdNLgFoCEdAliLhNyo4uXV9lChoBkdAUY4TpPhybWgHS/hoCEdAliNrTx5LRXV9lChoBkdAcIG8yeqaPWgHTSQBaAhHQJYkE6nzg/F1fZQoaAZHQHLxADRtxdZoB0v/aAhHQJYkJWfbsWx1fZQoaAZHQHC9AwGnn+1oB00vAWgIR0CWJJrLyMDPdX2UKGgGR0BzAWYtxuKoaAdL+WgIR0CWJLXhOxjbdX2UKGgGR0ByGD3Gn4wiaAdNWgFoCEdAliWWOAAhjnV9lChoBkdAbIX9roGIK2gHTW8BaAhHQJYl3rcCYC11fZQoaAZHQHDQqSowVTJoB00IAWgIR0CWJjQJokAxdX2UKGgGR0ByyXgsK9f1aAdNKgFoCEdAlij8ujASF3V9lChoBkdAcUVABDG96GgHTTIBaAhHQJYprT4L1Ep1fZQoaAZHQHF8twFTvRZoB002AWgIR0CWKyWmP5pKdX2UKGgGR0Bw7ToB7u2JaAdNYgFoCEdAliula4c3l3V9lChoBkdAcPtbONYKY2gHTRoBaAhHQJYr/+ERJ3B1fZQoaAZHQHEopKzzErJoB00QAWgIR0CWLEEYO2AodX2UKGgGR0ByEmNDMNc4aAdNNgFoCEdAli3T6WPcSHV9lChoBkdAcu78QI2OyWgHTRQBaAhHQJYvE4BFNL11fZQoaAZHQG/Jm8Empl1oB00nAWgIR0CWLyyXUpd9dX2UKGgGR0Bud6VD8cdYaAdNPAFoCEdAli9ElRgqmXV9lChoBkdAcer4S6DoQmgHTR0BaAhHQJYvo4ffXPJ1fZQoaAZHQHEP4yKvV3FoB01YAWgIR0CWL7Jr+HafdX2UKGgGR0Bw4YngHeJpaAdNFAFoCEdAljB0fYBeX3V9lChoBkdAcr25GjKxLWgHTUgBaAhHQJYwndcjZ+R1fZQoaAZHQHJqc/dIoVpoB00tAWgIR0CWMlZV4oqkdX2UKGgGR0BwRLuIAOriaAdL+mgIR0CWM/6jWTX8dX2UKGgGR0ByaZITXarWaAdNEgFoCEdAljXRxgiNbXV9lChoBkdATSTCxeLNwGgHS85oCEdAljilC5VfeHV9lChoBkdAbMEDNhVlw2gHTSUBaAhHQJY5G0u14Ph1fZQoaAZHQG9+lHrhR65oB00jAWgIR0CWOT6fJ3gUdX2UKGgGR0BwGvD3ueBhaAdNSwFoCEdAljpib2Dg63V9lChoBkdAbZ8Pvrnkk2gHTQkBaAhHQJY6rfVI7Nl1fZQoaAZHQHEWPFFUhmpoB00gAWgIR0CWO4ORDCxedX2UKGgGR0Bw1tPpIMBqaAdNIwFoCEdAljuOhsZYP3V9lChoBkdAcQk0knkT6GgHTQsBaAhHQJY73kcS5Ah1fZQoaAZHQHElN21UlzFoB00tAWgIR0CWPFXEZR8/dX2UKGgGR0BxO+uV5a/zaAdNVQFoCEdAljxg+IMz/XV9lChoBkdAcSnS2H+IdmgHS/ZoCEdAljy5S3solXV9lChoBkdAcBAmwaBI4GgHTT8BaAhHQJY9jMt9QXR1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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 Tue Jun 18 14:18:04 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 0x7bb899b5b920>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bb899b5b9c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bb899b5ba60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bb899b5bb00>", "_build": "<function ActorCriticPolicy._build at 0x7bb899b5bba0>", "forward": "<function ActorCriticPolicy.forward at 0x7bb899b5bc40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bb899b5bce0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bb899b5bd80>", "_predict": "<function ActorCriticPolicy._predict at 0x7bb899b5be20>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bb899b5bec0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bb899b5bf60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bb899b5c040>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bb899ef5d80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1742089795548883402, "learning_rate": 0.0003, "tensorboard_log": "runs/lunarlander", "_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 Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "False", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "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:b3ccf448cd707b6d793d69e0c473b83edbe8a266404c0456479f12ae90727c98
-size 148072
+oid sha256:4df633c283f071416a07cfc712fff9b8840e19b083404ced78493aaa6c3d40fb
+size 147625

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 0x7aff458ca0e0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7aff458ca170>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7aff458ca200>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7aff458ca290>",
-        "_build": "<function ActorCriticPolicy._build at 0x7aff458ca320>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7aff458ca3b0>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7aff458ca440>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7aff458ca4d0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7aff458ca560>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7aff458ca5f0>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7aff458ca680>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7aff458ca710>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7bb899b5b920>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bb899b5b9c0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bb899b5ba60>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bb899b5bb00>",
+        "_build": "<function ActorCriticPolicy._build at 0x7bb899b5bba0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7bb899b5bc40>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bb899b5bce0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bb899b5bd80>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7bb899b5be20>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bb899b5bec0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bb899b5bf60>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bb899b5c040>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7aff63e58280>"
+        "_abc_impl": "<_abc._abc_data object at 0x7bb899ef5d80>"
     },
     "verbose": 1,
     "policy_kwargs": {},
     "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "_total_timesteps": 1000000.0,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1719979071723113730,
+    "start_time": 1742089795548883402,
     "learning_rate": 0.0003,
-    "tensorboard_log": null,
+    "tensorboard_log": "runs/lunarlander",
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -45,7 +45,7 @@
     "_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'>",
@@ -87,13 +87,13 @@
     "n_epochs": 4,
     "clip_range": {
         ":type:": "<class 'function'>",
-        ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+        ":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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"
+        ":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:ad4781c4a8d1c8383a5563b439aeb3e4ce7fe00391e356385670cccba9f94c7a
-size 88362
+oid sha256:850cd14aa90a3f1b493e6a683b9dc21ffc1f0e7e9f44b2018bd6a8483a3db71c
+size 87978

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e36e735bcdd326cfc16a0f61ca94e20a8123d2b81bdbd61be426f625e6187ef2
-size 43762
+oid sha256:55b4b65fd59950a515019cf95cad12ab5f750c47ee094c18ab46a58dc7c2294a
+size 43634

ppo-LunarLander-v2/system_info.txt

@@ -1,9 +1,9 @@
-- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Tue Jun 18 14:18:04 UTC 2024
-- Python: 3.10.12
+- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
+- Python: 3.11.11
 - Stable-Baselines3: 2.0.0a5
-- PyTorch: 2.3.0+cu121
-- GPU Enabled: True
-- Numpy: 1.25.2
-- Cloudpickle: 2.2.1
+- PyTorch: 2.6.0+cu124
+- GPU Enabled: False
+- Numpy: 1.26.4
+- Cloudpickle: 3.1.1
 - Gymnasium: 0.28.1
 - OpenAI Gym: 0.25.2

results.json

@@ -1 +1 @@
-{"mean_reward": 257.9975279, "std_reward": 22.622947983072365, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-07-03T04:20:16.128601"}
+{"mean_reward": 237.58238336465166, "std_reward": 69.11912944466312, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-03-16T02:55:56.120090"}