BigTimeCoderSean commited on
Commit
0db022f
1 Parent(s): 985cc18

This is my lunar lander agent from class 1 of Hugging Face's RL class

Browse files
.gitattributes CHANGED
@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
28
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ - metrics:
12
+ - type: mean_reward
13
+ value: 191.74 +/- 31.06
14
+ name: mean_reward
15
+ task:
16
+ type: reinforcement-learning
17
+ name: reinforcement-learning
18
+ dataset:
19
+ name: LunarLander-v2
20
+ type: LunarLander-v2
21
+ ---
22
+
23
+ # **PPO** Agent playing **LunarLander-v2**
24
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
25
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
26
+
27
+ ## Usage (with Stable-baselines3)
28
+ TODO: Add your code
29
+
30
+
31
+ ```python
32
+ from stable_baselines3 import ...
33
+ from huggingface_sb3 import load_from_hub
34
+
35
+ ...
36
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7f16ae053710>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f16ae0537a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f16ae053830>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f16ae0538c0>", "_build": "<function ActorCriticPolicy._build at 0x7f16ae053950>", "forward": "<function ActorCriticPolicy.forward at 0x7f16ae0539e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f16ae053a70>", "_predict": "<function ActorCriticPolicy._predict at 0x7f16ae053b00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f16ae053b90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f16ae053c20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f16ae053cb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f16ae078180>"}, "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1657047922.0686255, "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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="}, "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "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 sha256:211b0d1b64ac738feb669dab3ce83d29720d0cf7ed87bb5763f9d4f612425e59
3
+ size 144140
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.0
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
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 0x7f16ae053710>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f16ae0537a0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f16ae053830>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f16ae0538c0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f16ae053950>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f16ae0539e0>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f16ae053a70>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f16ae053b00>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f16ae053b90>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f16ae053c20>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f16ae053cb0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f16ae078180>"
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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 16,
45
+ "num_timesteps": 507904,
46
+ "_total_timesteps": 500000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1657047922.0686255,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "gASVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="
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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 124,
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:c5302045b6a1214f776f7f6e4501636a8fc6d132329308cd6ec60589bc7812c7
3
+ size 84829
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7dc9a8d4bf0a8f38b4676571195f4dfc5bb1b13b568bdce38f7cb83c1ccadb71
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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
2
+ Python: 3.7.13
3
+ Stable-Baselines3: 1.5.0
4
+ PyTorch: 1.11.0+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3ce961215856d563c1ac6f6b1e18b74cdf701f989a05be2a3ece755b20413b8d
3
+ size 255468
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 191.73667465857295, "std_reward": 31.062055610565075, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-07-05T19:29:22.575678"}