Upload PPO LunarLander-v2 trained agent (10k steps)

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: -244.01 +/- 104.28
+      name: mean_reward
+      verified: false
+---
+
+# **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:": "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 0x7f8ef8935670>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8ef8935700>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8ef8935790>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8ef8935820>", "_build": "<function ActorCriticPolicy._build at 0x7f8ef89358b0>", "forward": "<function ActorCriticPolicy.forward at 0x7f8ef8935940>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8ef89359d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8ef8935a60>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8ef8935af0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8ef8935b80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8ef8935c10>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8ef8935ca0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f8ef892d870>"}, "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": 10000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1673798798050029605, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_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": -0.6384000000000001, "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-5.10.147+-x86_64-with-glibc2.27 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.0+cu116", "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 sha256:74cb56a110cfe9e983af57bacc49dbc4316d1242dd85ce919164dccdd0f1dbfc
+size 147284

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 0x7f8ef8935670>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8ef8935700>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8ef8935790>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8ef8935820>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f8ef89358b0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f8ef8935940>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8ef89359d0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8ef8935a60>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f8ef8935af0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8ef8935b80>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8ef8935c10>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8ef8935ca0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f8ef892d870>"
+    },
+    "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": 10000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1673798798050029605,
+    "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": -0.6384000000000001,
+    "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
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7bb3cae73f69e88a65b5c49a1e16beeac2a250e3ef9c6681a142090f10a48d96
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:91bfc8b1543d3568fd9d423efad21e7aeb69e0db1f98f44554306bef31d0b977
+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-5.10.147+-x86_64-with-glibc2.27 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
+- Python: 3.8.16
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.0+cu116
+- GPU Enabled: True
+- Numpy: 1.21.6
+- Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": -244.00701525814367, "std_reward": 104.28167947044166, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-15T16:08:56.164435"}