Rajaganapathy commited on
Commit
e4015ac
1 Parent(s): 62b4eb9

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: 237.11 +/- 50.89
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 0x7f762dd30af0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f762dd30b80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f762dd30c10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f762dd30ca0>", "_build": "<function ActorCriticPolicy._build at 0x7f762dd30d30>", "forward": "<function ActorCriticPolicy.forward at 0x7f762dd30dc0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f762dd30e50>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f762dd30ee0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f762dd30f70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f762dd33040>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f762dd330d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f762dd33160>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f762dd31b80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1682491350322962057, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_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:abb53828dc078312075c6b8716ea6f9a5eaf5980de4313b087f49cb00a6083c2
3
+ size 147387
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 0x7f762dd30af0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f762dd30b80>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f762dd30c10>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f762dd30ca0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f762dd30d30>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f762dd30dc0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f762dd30e50>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f762dd30ee0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f762dd30f70>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f762dd33040>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f762dd330d0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f762dd33160>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f762dd31b80>"
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": 1682491350322962057,
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:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
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 sha256:979cca29e769ac49cb5e3b004453cad09f64da3d07e77634d26c58c5471162ce
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:939a38f027f11bbc302ab4bab479b5b56e642116234cc5ee1b3158b79fd5b70f
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 (235 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 237.10584846205992, "std_reward": 50.892162611718696, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-26T07:18:51.528102"}