guluarte commited on
Commit
56a1517
1 Parent(s): 6d0d72b
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: 250.81 +/- 19.16
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 0x7f7bb16ed1f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7bb16ed280>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7bb16ed310>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7bb16ed3a0>", "_build": "<function ActorCriticPolicy._build at 0x7f7bb16ed430>", "forward": "<function ActorCriticPolicy.forward at 0x7f7bb16ed4c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7bb16ed550>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7bb16ed5e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7bb16ed670>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7bb16ed700>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7bb16ed790>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7bb16ed820>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7bb16e7810>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677882262673282494, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_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:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "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:c74f46fc88c30c887a53091065dcb7d85ca232da906bd3f9fadbd888f186ee86
3
+ size 147416
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,95 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7f7bb16ed1f0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7bb16ed280>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7bb16ed310>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7bb16ed3a0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f7bb16ed430>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f7bb16ed4c0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7bb16ed550>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7bb16ed5e0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f7bb16ed670>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7bb16ed700>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7bb16ed790>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7bb16ed820>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7f7bb16e7810>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "observation_space": {
25
+ ":type:": "<class 'gym.spaces.box.Box'>",
26
+ ":serialized:": "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",
27
+ "dtype": "float32",
28
+ "_shape": [
29
+ 8
30
+ ],
31
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
32
+ "high": "[inf inf inf inf inf inf inf inf]",
33
+ "bounded_below": "[False False False False False False False False]",
34
+ "bounded_above": "[False False False False False False False False]",
35
+ "_np_random": null
36
+ },
37
+ "action_space": {
38
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
39
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
40
+ "n": 4,
41
+ "_shape": [],
42
+ "dtype": "int64",
43
+ "_np_random": null
44
+ },
45
+ "n_envs": 16,
46
+ "num_timesteps": 1015808,
47
+ "_total_timesteps": 1000000,
48
+ "_num_timesteps_at_start": 0,
49
+ "seed": null,
50
+ "action_noise": null,
51
+ "start_time": 1677882262673282494,
52
+ "learning_rate": 0.0003,
53
+ "tensorboard_log": null,
54
+ "lr_schedule": {
55
+ ":type:": "<class 'function'>",
56
+ ":serialized:": "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"
57
+ },
58
+ "_last_obs": {
59
+ ":type:": "<class 'numpy.ndarray'>",
60
+ ":serialized:": "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"
61
+ },
62
+ "_last_episode_starts": {
63
+ ":type:": "<class 'numpy.ndarray'>",
64
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
65
+ },
66
+ "_last_original_obs": null,
67
+ "_episode_num": 0,
68
+ "use_sde": false,
69
+ "sde_sample_freq": -1,
70
+ "_current_progress_remaining": -0.015808000000000044,
71
+ "ep_info_buffer": {
72
+ ":type:": "<class 'collections.deque'>",
73
+ ":serialized:": "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"
74
+ },
75
+ "ep_success_buffer": {
76
+ ":type:": "<class 'collections.deque'>",
77
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
78
+ },
79
+ "_n_updates": 248,
80
+ "n_steps": 1024,
81
+ "gamma": 0.999,
82
+ "gae_lambda": 0.98,
83
+ "ent_coef": 0.01,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 4,
88
+ "clip_range": {
89
+ ":type:": "<class 'function'>",
90
+ ":serialized:": "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"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null
95
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:44d23902481d3376ef634433ba8541f23e6bce5461f09fa216b825af1f1b92ea
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5f26f12cbc11ffb940bc2fa3c9cd7f2fb3d38d669febfed4556b93efe2d9cdcf
3
+ size 43393
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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.10
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (243 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 250.80527240745505, "std_reward": 19.161438586848913, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-03T22:50:39.431060"}