Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -313.87 +/- 171.15
+      value: 270.67 +/- 24.43
       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 0x7fd9cd1f2280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd9cd1f2310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd9cd1f23a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd9cd1f2430>", "_build": "<function ActorCriticPolicy._build at 0x7fd9cd1f24c0>", "forward": "<function ActorCriticPolicy.forward at 0x7fd9cd1f2550>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd9cd1f25e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd9cd1f2670>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd9cd1f2700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd9cd1f2790>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd9cd1f2820>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd9cd1f28b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd9cd1f1980>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 32, "num_timesteps": 0, "_total_timesteps": 0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": null, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": null, "_last_episode_starts": null, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 1, "ep_info_buffer": null, "ep_success_buffer": null, "_n_updates": 0, "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:": "gAWV+QIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMYy9ob21lL3NhdXJhYmgvYW5hY29uZGEzL2VudnMvbGVhcm4tcmwvbGliL3B5dGhvbjMuOS9zaXRlLXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMYy9ob21lL3NhdXJhYmgvYW5hY29uZGEzL2VudnMvbGVhcm4tcmwvbGliL3B5dGhvbjMuOS9zaXRlLXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.15.0-58-generic-x86_64-with-glibc2.35 # 64-Ubuntu SMP Thu Jan 5 11:43:13 UTC 2023", "Python": "3.9.15", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu117", "GPU Enabled": "True", "Numpy": "1.22.3", "Gym": "0.21.0"}}
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param 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 0x7fd9cd1f2280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd9cd1f2310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd9cd1f23a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd9cd1f2430>", "_build": "<function ActorCriticPolicy._build at 0x7fd9cd1f24c0>", "forward": "<function ActorCriticPolicy.forward at 0x7fd9cd1f2550>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd9cd1f25e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd9cd1f2670>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd9cd1f2700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd9cd1f2790>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd9cd1f2820>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd9cd1f28b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd9cd1f1980>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 32, "num_timesteps": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1673827250829462578, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.15.0-58-generic-x86_64-with-glibc2.35 # 64-Ubuntu SMP Thu Jan 5 11:43:13 UTC 2023", "Python": "3.9.15", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu117", "GPU Enabled": "True", "Numpy": "1.22.3", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2e3d04f72cf3237b4d00fc31690a42c56cf7abfa5c178b8582737b810cf4821f
-size 53233
+oid sha256:1ba9b3450ddd14e54bc39a5d8257e7f4c27aa300e1d085eb576b57dbfde57aea
+size 148264

ppo-LunarLander-v2/data

@@ -43,28 +43,40 @@
         "_np_random": null
     },
     "n_envs": 32,
-    "num_timesteps": 0,
-    "_total_timesteps": 0,
+    "num_timesteps": 2031616,
+    "_total_timesteps": 2000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": null,
+    "start_time": 1673827250829462578,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"
     },
-    "_last_obs": null,
-    "_last_episode_starts": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="
+    },
     "_last_original_obs": null,
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": 1,
-    "ep_info_buffer": null,
-    "ep_success_buffer": null,
-    "_n_updates": 0,
+    "_current_progress_remaining": -0.015808000000000044,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 248,
     "n_steps": 1024,
     "gamma": 0.999,
     "gae_lambda": 0.98,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2497affac19a461e040f7a57c9a5933e93b10b5579b0a3d91d7d3978070520ec
-size 687
+oid sha256:b78e5302411e1300ec94ebc0ebd2ae74203bd9f7b2382c867568b2f787f51229
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cefd38098a0ed57941a986ad3908c5db77751a7be94b509dbdaaa4fe6a2c1227
+oid sha256:379d6f57bce5e66b1ef2ec9ada5b79da9f2265a886781da872e292eb77e32683
 size 43393

results.json

@@ -1 +1 @@
-{"mean_reward": -313.86818127389995, "std_reward": 171.15299321987615, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-15T23:58:14.272550"}
+{"mean_reward": 270.67248431160755, "std_reward": 24.43113679106701, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-16T03:38:54.676946"}