Upload PPO LunarLander-v2 trained agent

.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 +1,36 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 277.99 +/- 23.91
+      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 0x7f4f178d5320>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4f178d53b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4f178d5440>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4f178d54d0>", "_build": "<function ActorCriticPolicy._build at 0x7f4f178d5560>", "forward": "<function ActorCriticPolicy.forward at 0x7f4f178d55f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4f178d5680>", "_predict": "<function ActorCriticPolicy._predict at 0x7f4f178d5710>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4f178d57a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4f178d5830>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4f178d58c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f4f17922810>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1655068475.4871051, "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": 496, "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.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:92def6f6c94e64414264685c01f7686468000dd01f0d3d676be9d60dee578e80
+size 144118

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:": "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 0x7f4f178d5320>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4f178d53b0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4f178d5440>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4f178d54d0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f4f178d5560>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f4f178d55f0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4f178d5680>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f4f178d5710>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4f178d57a0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4f178d5830>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4f178d58c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f4f17922810>"
+    },
+    "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": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1655068475.4871051,
+    "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": 496,
+    "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:f88668a464ac42f2a5606b6632fbca38fc9efc548858332b5fc56175eb2c0ffd
+size 84893

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c4f6be37731bd11b22e3fe855012c5ac6eb6f4578e524d2c675530c2667be1b
+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:d7dfb9534cebe071d178d32dc891ad3ff1b69e507576e3e021300e99b420aa94
+size 186169

results.json

@@ -0,0 +1 @@
+{"mean_reward": 277.9923350750313, "std_reward": 23.908947305873145, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-12T21:30:24.524236"}