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

PPO_LunarLander.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8b745b45a9ed8e6859bc1969ed20c66e4a728fb041a669a785943288d34a6aac
+size 144216

PPO_LunarLander/_stable_baselines3_version

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

PPO_LunarLander/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 0x7f6d1d904950>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6d1d9049e0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6d1d904a70>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6d1d904b00>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f6d1d904b90>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f6d1d904c20>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6d1d904cb0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f6d1d904d40>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6d1d904dd0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6d1d904e60>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6d1d904ef0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f6d1d941e70>"
+    },
+    "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:": "gASVgQAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZRoB5OUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=",
+        "n": 4,
+        "shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "num_timesteps": 524288,
+    "_total_timesteps": 500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1656680655.1848364,
+    "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": -0.04857599999999995,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 160,
+    "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/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b00eedf205e1e048b13ce0b9925a9720bb83f592830499ec835e9ddca3f12276
+size 84893

PPO_LunarLander/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fa3a4c5131f5e2573e6955fc7901aff55509018cb274709a4706a2d22c350ab
+size 43201

PPO_LunarLander/pytorch_variables.pth

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

PPO_LunarLander/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: 0.17.3

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: 233.37 +/- 20.47
+      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 0x7f6d1d904950>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6d1d9049e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6d1d904a70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6d1d904b00>", "_build": "<function ActorCriticPolicy._build at 0x7f6d1d904b90>", "forward": "<function ActorCriticPolicy.forward at 0x7f6d1d904c20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6d1d904cb0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f6d1d904d40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6d1d904dd0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6d1d904e60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6d1d904ef0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f6d1d941e70>"}, "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:": "gASVgQAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZRoB5OUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=", "n": 4, "shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 524288, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1656680655.1848364, "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": -0.04857599999999995, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 160, "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-5.4.188+-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": "0.17.3"}}

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c33f5763bb708c9f7e86cc36823beac29484bb42824fc2839567f186e7d584d7
+size 248173

results.json

@@ -0,0 +1 @@
+{"mean_reward": 233.37053295809238, "std_reward": 20.471046111038987, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-07-01T13:17:42.067147"}