Galeros commited on
Commit
1116c4d
1 Parent(s): 2269f55

Upload PPO LunarLander-v2 trained agent

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - LunarLander-v2
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: PPO
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: LunarLander-v2
16
+ type: LunarLander-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 230.90 +/- 69.35
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
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 0x7f68a3d01cf0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f68a3d01d80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f68a3d01e10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f68a3d01ea0>", "_build": "<function ActorCriticPolicy._build at 0x7f68a3d01f30>", "forward": "<function ActorCriticPolicy.forward at 0x7f68a3d01fc0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f68a3d02050>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f68a3d020e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f68a3d02170>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f68a3d02200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f68a3d02290>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f68a3d02320>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f68a3cfe3c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1682622784349259601, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAACnnj12/my8rbIKvA60Dz1zGdA9NZ7ivQAAgD8AAIA/c58XvvafHTs+H4E7L+4luZXgurzjSRA6AACAPwAAgD8N7ta9w5VguiAL3zqnzjk2z1N+O4DNALoAAIA/AACAP5rKi7xcSyG60PjqOgZTrzXsRv45GvEEugAAgD8AAIA/zd5MPYaljD/y0cM98vjBvtmaiz0I5du8AAAAAAAAAABzP8m99kwXuuN9Kbrk2Ya13QpJO+a6RzkAAIA/AACAPwDyJ73hrKS6AD/qukR687U5c1q645wGOgAAgD8AAIA/zWDPvFy/XrqXc5u6pmwrtgiGATv70rI5AACAPwAAgD/N1Gs9rvWNumoMVLvggC+3Emi2OsMhdjoAAIA/AACAP00+Qj0fbbq5NY1tu+YLP7VK6bK7uYOPOgAAgD8AAIA/5r0nvRSGlroAdY+5flyFtBTA5rqn2aU4AACAPwAAgD8ALTO9XGscujLbhLn/+Sy2DGfROgadnzUAAIA/AACAPxqHfz6WiV0/4lucO/I1p74TpUI+q/yGvQAAAAAAAAAAM6P1OgOMPLx5pwI8cMgYPJCup73iXwI9AACAPwAAgD/N9FQ8XEtpusb2brv3hBU2zQSKO6sHh7UAAIA/AACAP1rtAL7XyDG7FaG9tkGPB7RkHDc8GAnuNQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.015808000000000044, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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, "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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f7b936a2ebaa6e4a57b94ffc074eb1667e3cca3b1771f015fa59d16d08a22a12
3
+ size 147388
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.8.0
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,96 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__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 ",
7
+ "__init__": "<function ActorCriticPolicy.__init__ at 0x7f68a3d01cf0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f68a3d01d80>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f68a3d01e10>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f68a3d01ea0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f68a3d01f30>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f68a3d01fc0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f68a3d02050>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f68a3d020e0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f68a3d02170>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f68a3d02200>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f68a3d02290>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f68a3d02320>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f68a3cfe3c0>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1015808,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1682622784349259601,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "lr_schedule": {
33
+ ":type:": "<class 'function'>",
34
+ ":serialized:": "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"
35
+ },
36
+ "_last_obs": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "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"
39
+ },
40
+ "_last_episode_starts": {
41
+ ":type:": "<class 'numpy.ndarray'>",
42
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
43
+ },
44
+ "_last_original_obs": null,
45
+ "_episode_num": 0,
46
+ "use_sde": false,
47
+ "sde_sample_freq": -1,
48
+ "_current_progress_remaining": -0.015808000000000044,
49
+ "_stats_window_size": 100,
50
+ "ep_info_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "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"
53
+ },
54
+ "ep_success_buffer": {
55
+ ":type:": "<class 'collections.deque'>",
56
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
57
+ },
58
+ "_n_updates": 248,
59
+ "observation_space": {
60
+ ":type:": "<class 'gym.spaces.box.Box'>",
61
+ ":serialized:": "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",
62
+ "dtype": "float32",
63
+ "_shape": [
64
+ 8
65
+ ],
66
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
67
+ "high": "[inf inf inf inf inf inf inf inf]",
68
+ "bounded_below": "[False False False False False False False False]",
69
+ "bounded_above": "[False False False False False False False False]",
70
+ "_np_random": null
71
+ },
72
+ "action_space": {
73
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
74
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
75
+ "n": 4,
76
+ "_shape": [],
77
+ "dtype": "int64",
78
+ "_np_random": null
79
+ },
80
+ "n_envs": 16,
81
+ "n_steps": 1024,
82
+ "gamma": 0.999,
83
+ "gae_lambda": 0.98,
84
+ "ent_coef": 0.01,
85
+ "vf_coef": 0.5,
86
+ "max_grad_norm": 0.5,
87
+ "batch_size": 64,
88
+ "n_epochs": 4,
89
+ "clip_range": {
90
+ ":type:": "<class 'function'>",
91
+ ":serialized:": "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"
92
+ },
93
+ "clip_range_vf": null,
94
+ "normalize_advantage": true,
95
+ "target_kl": null
96
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:93348439290cb7b489f9c4281108d82878d8e62920df2ce3166e7b7214d91fd5
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5ed20edc7a673805daf1809394d41984bd4a5874887fa8a5122096b587aaf98a
3
+ size 43329
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.10.11
3
+ - Stable-Baselines3: 1.8.0
4
+ - PyTorch: 2.0.0+cu118
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (215 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 230.89565957730065, "std_reward": 69.35351907924611, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-27T19:48:09.894538"}