lotek93 commited on
Commit
c67567b
·
1 Parent(s): ea5c44e

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: 246.72 +/- 40.12
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 0x7ff16ca8a040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff16ca8a0d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff16ca8a160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff16ca8a1f0>", "_build": "<function ActorCriticPolicy._build at 0x7ff16ca8a280>", "forward": "<function ActorCriticPolicy.forward at 0x7ff16ca8a310>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff16ca8a3a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff16ca8a430>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff16ca8a4c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff16ca8a550>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff16ca8a5e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff16ca8a670>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ff16ca8c080>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1682234080020918315, "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, "_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": "3.9.16", "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 sha256:06642a48286d9989bd0f38aa76572d8c64b0c8edba668714f07265144ae175dc
3
+ size 147347
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 0x7ff16ca8a040>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff16ca8a0d0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff16ca8a160>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff16ca8a1f0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7ff16ca8a280>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7ff16ca8a310>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff16ca8a3a0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff16ca8a430>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7ff16ca8a4c0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff16ca8a550>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff16ca8a5e0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff16ca8a670>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7ff16ca8c080>"
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": 1682234080020918315,
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 sha256:970c82425617ae980f39c997270dc1e5504f38be06247486709a9b93e4f9c670
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:527b1d63a7eba9fb09fd2cb57bf9833aeab65a678122074ca7b2a7fb8bf912c3
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: 3.9.16
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 (231 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 246.72320632788515, "std_reward": 40.120324153513984, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-23T07:35:01.536789"}