yyfairstein commited on
Commit
8d17c28
·
1 Parent(s): 8b44a61

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: 235.12 +/- 7.43
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 0x7f2a7b502f70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2a7b506040>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2a7b5060d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2a7b506160>", "_build": "<function ActorCriticPolicy._build at 0x7f2a7b5061f0>", "forward": "<function ActorCriticPolicy.forward at 0x7f2a7b506280>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2a7b506310>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2a7b5063a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2a7b506430>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2a7b5064c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2a7b506550>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2a7b4ff750>"}, "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": 1672298513553332617, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAKaGfj5rDkw/WAb9PV/+sL6GORo+oEd7vQAAAAAAAAAAgB85vcMsUz2enyK9/0pfvqD8p70lgF49AAAAAAAAAACAOD299rwiuo5u5DoVShE2DPUeutKiBroAAIA/AACAP82yMD32bF26nkPIORXL87X52bW5CBjruAAAgD8AAIA/ZsUQPR/tprlufTs5EVdMNHXoLzmVMVu4AACAPwAAgD+mnVk+bC3ou4ERqL2eYk++/m77PdSDDT8AAIA/AACAP037vj3DsSO6AihrORGFLTVzTM07wgaJuAAAgD8AAIA/erxZPnRSGD75AEm+/Sd/viEa8bxJSI29AAAAAAAAAABm1OM8KZRbuhnphjoCzX81qsCCO4IOm7kAAIA/AACAPzNRPLyPngi6QByPuTMbPLNHg2K7SjqpOAAAgD8AAIA/Mwl6POzZsrk4Kc46ZpaBNYKQybkmmu25AACAPwAAgD8zv5S7ttciPWvQ4j0TYoK+xmJEPY2Lzb0AAAAAAAAAAPae2T7aqYI/n6KHPfVwj76apzU+cRI0vQAAAAAAAAAAmhV7PVIYsTg6UTO7OlMGtmg9WziAHVY6AACAPwAAgD9NsSK9w/FeusxxqDubnYo45iBFOodnKbkAAIA/AACAP01BC70pYH26K9UTul2dVDagF0u7o0EpOQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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:f2d3102f3170426e3c4e47a8c66ef2fe7518201e66c988d5221608c013582f55
3
+ size 147206
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 0x7f2a7b502f70>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2a7b506040>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2a7b5060d0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2a7b506160>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f2a7b5061f0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f2a7b506280>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2a7b506310>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f2a7b5063a0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2a7b506430>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2a7b5064c0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2a7b506550>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f2a7b4ff750>"
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": 1672298513553332617,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
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 sha256:4811a4ddef4ae11a695b1a4d4579d3669bcb308af8bcd4fb15afa75d5bb4e342
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:84ec54dcc43f4053ecb83c0c40d5e7de644610eab9323cc675990c449c2be360
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 (262 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 235.12126323792023, "std_reward": 7.4326695291841505, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-29T07:45:24.605556"}