Upload PPO Lunar Lander V2

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: -3498.72 +/- 3114.72
+      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 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 0x7ff070a409d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff070a40a60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff070a40af0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff070a40b80>", "_build": "<function ActorCriticPolicy._build at 0x7ff070a40c10>", "forward": "<function ActorCriticPolicy.forward at 0x7ff070a40ca0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff070a40d30>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff070a40dc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff070a40e50>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff070a40ee0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff070a40f70>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff070a36fc0>"}, "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": 65536, "_total_timesteps": 50000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671970652985035022, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAE2cfT17LUo/Et08PsviJ7+YwV6+GkG/vQAAAAAAAAAAs3DivZIBpz8mP8m+RlaavnSYqjw+d4y9AAAAAAAAAAAaQKU+LMAcPuZcn77fF5e/2QKWPfe1Q74AAAAAAAAAAJ1r0z5qx3I+AjkSPSWTjb+BT4k+XTmHvAAAAAAAAAAAbQSWvk9CeD7LfGi+ZM93v8Nb1b5K0JO+AAAAAAAAAACNA7S9PHuSP4XFsr6BwuS+gq6TPvMUe70AAAAAAAAAAM04EL1irsE/iNjwvUL4qr4W+qA+ejWAPgAAAAAAAAAAM+PJukQsnj/jDGc8miIRv43gib1lQWS+AAAAAAAAAABmVHu8Z1sMvf3RHr6CQpG/xS9WvSi8oL4AAIA/AACAP82Oyryw1LI/+NR+vvPjv70UOh07Hzi5vAAAAAAAAAAAGkpbPewhnz9DQ6Y+OVYSv0qdaD0qghQ+AAAAAAAAAACa1My8NlJzP/ixLb7U3B+/uT2kPjh4Wz4AAAAAAAAAALNs2j1Dub4/mXa7PozyX72sz2c+8uZ2PgAAAAAAAAAAmrExPRVWoT/1554+ZGUjvxIitTliIF48AAAAAAAAAABwPM8+LCNCP2alvT4E+3G/sonIPj0Qhj4AAAAAAAAAAGZpED4yVpg/wuLIPrK1Ar8UcI+9n0wbPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": -0.3107200000000001, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 30, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "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 sha256:8eaeb99f1b78f39579400c8e78843d5b3859d6caf781acb45a31b849ecd2a084
+size 147078

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.2

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 0x7ff070a409d0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff070a40a60>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff070a40af0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff070a40b80>",
+        "_build": "<function ActorCriticPolicy._build at 0x7ff070a40c10>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7ff070a40ca0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff070a40d30>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7ff070a40dc0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff070a40e50>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff070a40ee0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff070a40f70>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7ff070a36fc0>"
+    },
+    "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": 65536,
+    "_total_timesteps": 50000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1671970652985035022,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+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": -0.3107200000000001,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 30,
+    "n_steps": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 10,
+    "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 sha256:7298fb1da67b6d67458b00d99f13521766ce29e7b87e664465c0b0aaf5daafe9
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5c9f252366ad515250ff8e8232cde209ae0458ed9b66c344d0898df74d90a8eb
+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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.8.16
+Stable-Baselines3: 1.6.2
+PyTorch: 1.13.0+cu116
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": -3498.722371591709, "std_reward": 3114.7199383374964, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-25T12:19:53.850955"}