mmoallem commited on
Commit
bfda41c
1 Parent(s): b56240e

Upload MM 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: 256.73 +/- 21.75
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 0x7fc31c6cc160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc31c6cc1f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc31c6cc280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc31c6cc310>", "_build": "<function ActorCriticPolicy._build at 0x7fc31c6cc3a0>", "forward": "<function ActorCriticPolicy.forward at 0x7fc31c6cc430>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc31c6cc4c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc31c6cc550>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc31c6cc5e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc31c6cc670>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc31c6cc700>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc31c6cc790>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fc31c6ce100>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1679322543995432342, "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"}}
mm-ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:927b8677874b4446585fdf6d7c13fecc58abf023d6e2c1c5f4a250219843bf9d
3
+ size 147425
mm-ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
mm-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 0x7fc31c6cc160>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc31c6cc1f0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc31c6cc280>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc31c6cc310>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fc31c6cc3a0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fc31c6cc430>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc31c6cc4c0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc31c6cc550>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fc31c6cc5e0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc31c6cc670>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc31c6cc700>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc31c6cc790>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7fc31c6ce100>"
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": 1679322543995432342,
52
+ "learning_rate": 0.0003,
53
+ "tensorboard_log": null,
54
+ "lr_schedule": {
55
+ ":type:": "<class 'function'>",
56
+ ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null
95
+ }
mm-ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ede6d32042200d1b78ad5ba481a95324695a332dd3311284e62d111ee386000e
3
+ size 87929
mm-ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:49978f78ac7fc71edfd69789110e237829e4218399a0e465e2bc798f4da47b56
3
+ size 43393
mm-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
mm-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 (208 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 256.7251196880567, "std_reward": 21.749474306917833, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-20T15:00:09.478611"}