nutjung commited on
Commit
2075a48
1 Parent(s): 99b8366

Upload PPO LunarLander-v2 trained agent

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: 273.94 +/- 14.80
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 0x7f9b4e09f200>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9b4e09f290>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9b4e09f320>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9b4e09f3b0>", "_build": "<function ActorCriticPolicy._build at 0x7f9b4e09f440>", "forward": "<function ActorCriticPolicy.forward at 0x7f9b4e09f4d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9b4e09f560>", "_predict": "<function ActorCriticPolicy._predict at 0x7f9b4e09f5f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9b4e09f680>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9b4e09f710>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9b4e09f7a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f9b4e0ee4b0>"}, "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": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1654377490.844857, "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": -0.004885333333333408, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 184, "n_steps": 2048, "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:eaf46813c1f57b5d3f2ae1976d85f32bab3d58d73945113837c98a33c83d36b7
3
+ size 144153
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 0x7f9b4e09f200>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9b4e09f290>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9b4e09f320>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9b4e09f3b0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f9b4e09f440>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f9b4e09f4d0>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9b4e09f560>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f9b4e09f5f0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9b4e09f680>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9b4e09f710>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9b4e09f7a0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f9b4e0ee4b0>"
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": 1507328,
46
+ "_total_timesteps": 1500000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1654377490.844857,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "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"
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": -0.004885333333333408,
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": 184,
79
+ "n_steps": 2048,
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:e2f6cb0974462534ab61126027ffa50a0694a94210346d4ce9eec00c8ae469be
3
+ size 84893
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:10d244392f27c8aa9528cb764277a699953b99150273b4c234b9356424ade49f
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 sha256:4b36992323df861081594316a8079416ffffc8ecaaa38cfdc1473e0fa0392680
3
+ size 230083
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 273.9426393888357, "std_reward": 14.800940320789147, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-04T22:08:16.676942"}