tayfen commited on
Commit
4dde544
·
1 Parent(s): 84d4eca

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: 241.25 +/- 20.45
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 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 0x7fe6e7cce790>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe6e7cce820>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe6e7cce8b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe6e7cce940>", "_build": "<function ActorCriticPolicy._build at 0x7fe6e7cce9d0>", "forward": "<function ActorCriticPolicy.forward at 0x7fe6e7ccea60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe6e7cceaf0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe6e7cceb80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe6e7ccec10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe6e7cceca0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe6e7cced30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe6e7cc2d20>"}, "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": 1671114230991859322, "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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "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:ebd9dce86d1300fc2f1a21ffd13719a23bf2d47665b65bedbc0a6a59709031e2
3
+ size 147178
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.2
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 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 ",
7
+ "__init__": "<function ActorCriticPolicy.__init__ at 0x7fe6e7cce790>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe6e7cce820>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe6e7cce8b0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe6e7cce940>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fe6e7cce9d0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fe6e7ccea60>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe6e7cceaf0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fe6e7cceb80>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe6e7ccec10>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe6e7cceca0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe6e7cced30>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fe6e7cc2d20>"
20
+ },
21
+ "verbose": 1,
22
+ "policy_kwargs": {},
23
+ "observation_space": {
24
+ ":type:": "<class 'gym.spaces.box.Box'>",
25
+ ":serialized:": "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",
26
+ "dtype": "float32",
27
+ "_shape": [
28
+ 8
29
+ ],
30
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
31
+ "high": "[inf inf inf inf inf inf inf inf]",
32
+ "bounded_below": "[False False False False False False False False]",
33
+ "bounded_above": "[False False False False False False False False]",
34
+ "_np_random": null
35
+ },
36
+ "action_space": {
37
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
38
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 16,
45
+ "num_timesteps": 1015808,
46
+ "_total_timesteps": 1000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1671114230991859322,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "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"
56
+ },
57
+ "_last_obs": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "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"
60
+ },
61
+ "_last_episode_starts": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
64
+ },
65
+ "_last_original_obs": null,
66
+ "_episode_num": 0,
67
+ "use_sde": false,
68
+ "sde_sample_freq": -1,
69
+ "_current_progress_remaining": -0.015808000000000044,
70
+ "ep_info_buffer": {
71
+ ":type:": "<class 'collections.deque'>",
72
+ ":serialized:": "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"
73
+ },
74
+ "ep_success_buffer": {
75
+ ":type:": "<class 'collections.deque'>",
76
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 248,
79
+ "n_steps": 1024,
80
+ "gamma": 0.999,
81
+ "gae_lambda": 0.98,
82
+ "ent_coef": 0.01,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 4,
87
+ "clip_range": {
88
+ ":type:": "<class 'function'>",
89
+ ":serialized:": "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"
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:32ee32fdd43718fb60a07e2fa76156a50a240fb23e5d2b478c841ec512e2ca71
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:265992cc308d65a079d7fb96b9d4fd60d2fd22ab953b4fa4e551508c59cd9429
3
+ size 43201
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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
2
+ Python: 3.8.16
3
+ Stable-Baselines3: 1.6.2
4
+ PyTorch: 1.13.0+cu116
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
Binary file (249 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 241.2535966142053, "std_reward": 20.446978743744303, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-15T15:00:43.036779"}