Ellipsoul commited on
Commit
9e02012
·
1 Parent(s): 772cb40

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: 276.53 +/- 15.58
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 0x7f4740590160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f47405901f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4740590280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4740590310>", "_build": "<function ActorCriticPolicy._build at 0x7f47405903a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f4740590430>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f47405904c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4740590550>", "_predict": "<function ActorCriticPolicy._predict at 0x7f47405905e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4740590670>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4740590700>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4740590790>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f4740596200>"}, "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": 1679086767910062945, "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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "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:ca7507c34b31ce7abcf3909d70101d887057ffc5001b60d4a8fe08d080b63c79
3
+ size 147333
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 0x7f4740590160>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f47405901f0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4740590280>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4740590310>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f47405903a0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f4740590430>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f47405904c0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4740590550>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f47405905e0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4740590670>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4740590700>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4740590790>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f4740596200>"
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": 1679086767910062945,
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:a95d69e776e1276310a0dfd61a3fa7d0cea305a80513422157242b57f84de0f5
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:538901b661c56ee3268a6d2876fe1097018566245ee459cf3716568af7069e03
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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.9.16
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 (236 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 276.53406471675953, "std_reward": 15.576346546692882, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-17T21:20:54.655123"}