First PPO Model trained on LunarLander-V2

PPO-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:954d77329631b2043c37ee395887012bee457b2df4cf0f9299c410c9622c7311
+size 147614

PPO-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.7.0

PPO-LunarLander-v2/data

@@ -0,0 +1,95 @@
+{
+    "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 0x7f4676a69790>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4676a69820>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4676a698b0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4676a69940>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f4676a699d0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f4676a69a60>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4676a69af0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4676a69b80>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f4676a69c10>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4676a69ca0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4676a69d30>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4676a69dc0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f4676a6d140>"
+    },
+    "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": 16,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1677286444352056059,
+    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_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
+}

PPO-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6510377d4233d3be3f357fac7c033167edb85447fadea0f640e6131cb2ea3194
+size 88057

PPO-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e7470aba8122790ba69dd9dc3c426dc1a8eabc92d23196c2f2017cb78cdfe945
+size 43393

PPO-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

PPO-LunarLander-v2/system_info.txt

@@ -0,0 +1,7 @@
+- OS: Linux-5.19.0-32-generic-x86_64-with-glibc2.31 # 33~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon Jan 30 17:03:34 UTC 2
+- Python: 3.9.16
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu117
+- GPU Enabled: True
+- Numpy: 1.24.2
+- Gym: 0.21.0

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 256.23 +/- 17.59
+      value: 261.22 +/- 19.14
       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 0x7f29629ced30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f29629cedc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f29629cee50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f29629ceee0>", "_build": "<function ActorCriticPolicy._build at 0x7f29629cef70>", "forward": "<function ActorCriticPolicy.forward at 0x7f29629d3040>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f29629d30d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f29629d3160>", "_predict": "<function ActorCriticPolicy._predict at 0x7f29629d31f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f29629d3280>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f29629d3310>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f29629d33a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f29629d0270>"}, "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": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677339703106862956, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "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 0x7f4676a69790>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4676a69820>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4676a698b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4676a69940>", "_build": "<function ActorCriticPolicy._build at 0x7f4676a699d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f4676a69a60>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4676a69af0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4676a69b80>", "_predict": "<function ActorCriticPolicy._predict at 0x7f4676a69c10>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4676a69ca0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4676a69d30>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4676a69dc0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f4676a6d140>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677286444352056059, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_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-5.19.0-32-generic-x86_64-with-glibc2.31 # 33~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon Jan 30 17:03:34 UTC 2", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu117", "GPU Enabled": "True", "Numpy": "1.24.2", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": 256.2339051785674, "std_reward": 17.594155066877402, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-25T16:17:59.386843"}
+{"mean_reward": 261.2160120517673, "std_reward": 19.14079581722797, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-26T01:35:30.268066"}