HF RL unit1: ppo LunarLander-v2 baseline 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: 258.75 +/- 26.92
+      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 0x7fabdd5390e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fabdd539170>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fabdd539200>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fabdd539290>", "_build": "<function ActorCriticPolicy._build at 0x7fabdd539320>", "forward": "<function ActorCriticPolicy.forward at 0x7fabdd5393b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fabdd539440>", "_predict": "<function ActorCriticPolicy._predict at 0x7fabdd5394d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fabdd539560>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fabdd5395f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fabdd539680>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fabdd58f4e0>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1655065015.7573557, "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": 310, "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": 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"}}

lunar_lander_mlp_10epoch.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:971a5595ea9cbb432eb2e2fa9a722288b739d640998a45f82b8aaf3c824968f4
+size 144203

lunar_lander_mlp_10epoch/_stable_baselines3_version

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

lunar_lander_mlp_10epoch/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 0x7fabdd5390e0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fabdd539170>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fabdd539200>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fabdd539290>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fabdd539320>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fabdd5393b0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fabdd539440>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fabdd5394d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fabdd539560>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fabdd5395f0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fabdd539680>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fabdd58f4e0>"
+    },
+    "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": 507904,
+    "_total_timesteps": 500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1655065015.7573557,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gASVjQIAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxBLCIaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUIAAgAApo65PSlYf7qKXSs8PaX7NSCr1rr7nvQ0AAAAAAAAgD9za+g9w1kzugZj2rkt2qa3ek94urOahDcAAIA/AACAP2aEJz7hyuE5AzUluQvqn7UyGOo74axDOAAAgD8AAIA/QNCLPcP9W7ph9QE6d1PdtS9g9LqH0hi5AACAPwAAgD+m99k9jw4sugwikrpWYpO1gYrKOlXfqjkAAIA/AACAP01tNj32zFG645aTOxxLkTYdXOQ4KhyONQAAgD8AAIA/TatQvdcTDrlPMKw67X06NqP9tDsiOM65AACAPwAAgD+Agwe94aSCulaMOLvmNiy2LifXOl5eVzoAAIA/AACAP1r35r0fneq5g9sLPAUlKDXc5z+6tSwzNAAAgD8AAAAAxlrTPhdECT6eNNy5+sWYuLZbNj5+fWg5AAAAAAAAgD8z2Wy8uG6/uYjdwjpQYVo2DjPuO5hG5rkAAIA/AACAP8D4EL6unaC6/ocZvOWlmjxMIps8D5mFvQAAgD8AAIA/M3qAPXvimbrK6A077cwmNr0mnToa9x81AACAPwAAgD9gFx0+QG+8Pq6iG76djrW+UfyoPLkcNL0AAAAAAAAAACZ9HD6uC4s/GKbvPkIu0L6YBsE9i5BcPgAAAAAAAAAAAE1+veyIbT8MpYi9LOThvlW1ir3Yct28AAAAAAAAAACUdJRiLg=="
+    },
+    "_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": 310,
+    "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": 10,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null
+}

lunar_lander_mlp_10epoch/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:081a99b5c3901d6dd292731ea3ce3b1cc1189c4f331d98b41f7eb4e9155f0791
+size 84893

lunar_lander_mlp_10epoch/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9cbf9a47f7caf511707a9bd42a88fe42648e20715a9830b17cd8a23ec05ff3a5
+size 43201

lunar_lander_mlp_10epoch/pytorch_variables.pth

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

lunar_lander_mlp_10epoch/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

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fd92f732bf1be406497da986d0553bd2d70f2f677e0e3c63a9022bb7a600a3ef
+size 217218

results.json

@@ -0,0 +1 @@
+{"mean_reward": 258.74795485992865, "std_reward": 26.92412651050815, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-12T20:29:18.483167"}