First model

.gitattributes

@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,28 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: -186.66 +/- 90.03
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+---
+
+  # **PPO** Agent playing **LunarLander-v2**
+  This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+  
+  ## Usage (with Stable-baselines3)
+  TODO: Add your code
+  

config.json

@@ -0,0 +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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7efb1205e290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efb1205e320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efb1205e3b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efb1205e440>", "_build": "<function ActorCriticPolicy._build at 0x7efb1205e4d0>", "forward": "<function ActorCriticPolicy.forward at 0x7efb1205e560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efb1205e5f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7efb1205e680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efb1205e710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efb1205e7a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efb1205e830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7efb120ac750>"}, "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": 16384, "_total_timesteps": 100, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652626913.8750818, "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": -162.84, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 4, "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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2-test.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cc60ab6d100524088ab7c24708097230a0b00607bdb70d94b1d38833782470eb
+size 143896

ppo-LunarLander-v2-test/_stable_baselines3_version

@@ -0,0 +1 @@
+1.5.0

ppo-LunarLander-v2-test/data

@@ -0,0 +1,94 @@
+{
+    "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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7efb1205e290>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efb1205e320>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efb1205e3b0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efb1205e440>",
+        "_build": "<function ActorCriticPolicy._build at 0x7efb1205e4d0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7efb1205e560>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efb1205e5f0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7efb1205e680>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efb1205e710>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efb1205e7a0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efb1205e830>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7efb120ac750>"
+    },
+    "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": 16384,
+    "_total_timesteps": 100,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1652626913.8750818,
+    "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": -162.84,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 4,
+    "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:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null
+}

ppo-LunarLander-v2-test/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5cd09e6abe959fad37d6319e697940cd9ecd219be96cf1732b2aeaae37228d12
+size 84829

ppo-LunarLander-v2-test/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:98d18bb53a3dea02255e44ae3d18f0bc57f5f57cfd1df646d2b2701eba19492c
+size 43201

ppo-LunarLander-v2-test/pytorch_variables.pth

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

ppo-LunarLander-v2-test/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.5.0
+PyTorch: 1.11.0+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:89078b0c9d949b75c37c2a9ed8d776e3a492a309fce7020fa87f3edb4dbe3d5e
+size 144039

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.5.0

ppo-LunarLander-v2/data

@@ -0,0 +1,94 @@
+{
+    "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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f2262ae2050>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2262ae20e0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2262ae2170>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2262ae2200>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f2262ae2290>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f2262ae2320>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2262ae23b0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f2262ae2440>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2262ae24d0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2262ae2560>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2262ae25f0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f2262b381b0>"
+    },
+    "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": 507904,
+    "_total_timesteps": 500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1652625000.310725,
+    "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": 128,
+    "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:bf8a0ac5ad6d725a85b5a5b983b1cc341cf64b4e757606811d94aab2dcd350bf
+size 84829

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:00dd258b847031950d0e17121eeb54024b4c0c141263a09a7df0d9f09245edcb
+size 43201

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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.5.0
+PyTorch: 1.11.0+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f94b4e002982db8b2bafef40eb9d077dbc62123c22ed212be4ff242bf3c8ab0c
+size 258457

results.json

@@ -0,0 +1 @@
+{"mean_reward": -186.65593327616807, "std_reward": 90.03471367696005, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-15T15:02:12.485921"}