Upload PPO LunarLander-v2 trained agent

README.md

@@ -0,0 +1,36 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 188.33 +/- 31.64
+      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
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

@@ -0,0 +1 @@
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7f75d04ec8c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f75d04ec950>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f75d04ec9e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f75d04eca70>", "_build": "<function ActorCriticPolicy._build at 0x7f75d04ecb00>", "forward": "<function ActorCriticPolicy.forward at 0x7f75d04ecb90>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f75d04ecc20>", "_predict": "<function ActorCriticPolicy._predict at 0x7f75d04eccb0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f75d04ecd40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f75d04ecdd0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f75d04ece60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f75d04c4420>"}, "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1659460869.9042206, "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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="}, "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "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:": "gASVXwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX2ZpbGxfZnVuY3Rpb26Uk5QoaACMD19tYWtlX3NrZWxfZnVuY5STlGgAjA1fYnVpbHRpbl90eXBllJOUjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlEsBfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdYeUUpR9lCiMB2dsb2JhbHOUfZSMCGRlZmF1bHRzlE6MBGRpY3SUfZSMDmNsb3N1cmVfdmFsdWVzlF2URz/JmZmZmZmaYYwGbW9kdWxllGgZjARuYW1llGgPjANkb2OUTowXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC2Fubm90YXRpb25zlH2UjAhxdWFsbmFtZZSMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjAprd2RlZmF1bHRzlE51dFIu"}, "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": "1.6.0", "PyTorch": "1.12.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2-cs.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8c6ca881fa590f7607f6aee02856a7b587bd81b4517676e0d8509c8ae0716581
+size 146996

ppo-LunarLander-v2-cs/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.0

ppo-LunarLander-v2-cs/data

@@ -0,0 +1,94 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
+        "__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 0x7f75d04ec8c0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f75d04ec950>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f75d04ec9e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f75d04eca70>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f75d04ecb00>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f75d04ecb90>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f75d04ecc20>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f75d04eccb0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f75d04ecd40>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f75d04ecdd0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f75d04ece60>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f75d04c4420>"
+    },
+    "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1659460869.9042206,
+    "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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="
+    },
+    "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 124,
+    "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-cs/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5741cf64a33d07f2bf8064dd1f5b6eb8289d0bed323283a0e78f5f7f34610687
+size 87865

ppo-LunarLander-v2-cs/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:850f52058b1d022dbd15d3918896476604b94296ecf0d9c6693102bb7709ebb3
+size 43201

ppo-LunarLander-v2-cs/pytorch_variables.pth

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

ppo-LunarLander-v2-cs/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: 1.6.0
+PyTorch: 1.12.0+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 188.32714400008246, "std_reward": 31.640746716532547, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-08-02T17:47:37.249088"}