Sartc commited on
Commit
04c76e2
·
1 Parent(s): 2d1acca

push lunar lander to hub

Browse files
.gitattributes CHANGED
@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
32
  *.zip filter=lfs diff=lfs merge=lfs -text
33
  *.zst filter=lfs diff=lfs merge=lfs -text
34
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
32
  *.zip filter=lfs diff=lfs merge=lfs -text
33
  *.zst filter=lfs diff=lfs merge=lfs -text
34
  *tfevents* filter=lfs diff=lfs merge=lfs -text
35
+ replay.mp4 filter=lfs diff=lfs merge=lfs -text
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: -402.40 +/- 104.21
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 0x7fd73bf4a9d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd73bf4aa60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd73bf4aaf0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd73bf4ab80>", "_build": "<function ActorCriticPolicy._build at 0x7fd73bf4ac10>", "forward": "<function ActorCriticPolicy.forward at 0x7fd73bf4aca0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd73bf4ad30>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd73bf4adc0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd73bf4ae50>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd73bf4aee0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd73bf4af70>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd73bf4d040>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fd73bf4b150>"}, "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": 32768, "_total_timesteps": 500, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1675283116709994769, "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": -64.536, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 10, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "False", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-luanr-lander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7c2f5f82003a18dccde12e856e9eac0bf4338ac40eac097b21a92fbd117eb833
3
+ size 146759
ppo-luanr-lander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
ppo-luanr-lander-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 0x7fd73bf4a9d0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd73bf4aa60>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd73bf4aaf0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd73bf4ab80>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fd73bf4ac10>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fd73bf4aca0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd73bf4ad30>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd73bf4adc0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fd73bf4ae50>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd73bf4aee0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd73bf4af70>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd73bf4d040>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7fd73bf4b150>"
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": 32768,
47
+ "_total_timesteps": 500,
48
+ "_num_timesteps_at_start": 0,
49
+ "seed": null,
50
+ "action_noise": null,
51
+ "start_time": 1675283116709994769,
52
+ "learning_rate": 0.0003,
53
+ "tensorboard_log": null,
54
+ "lr_schedule": {
55
+ ":type:": "<class 'function'>",
56
+ ":serialized:": "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"
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": -64.536,
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": 10,
80
+ "n_steps": 2048,
81
+ "gamma": 0.99,
82
+ "gae_lambda": 0.95,
83
+ "ent_coef": 0.0,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 10,
88
+ "clip_range": {
89
+ ":type:": "<class 'function'>",
90
+ ":serialized:": "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"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null
95
+ }
ppo-luanr-lander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d8b519a52b09035568e07325456b25105c2d982cdd08085d38a58b7719d7815e
3
+ size 87545
ppo-luanr-lander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b25a15f7eb97c24761f2788501606f173c8fb2c40696c5c153eb2305a897c4f2
3
+ size 43265
ppo-luanr-lander-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-luanr-lander-v2/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.10
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: False
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:f9ec47d3aeff4dd176afb63ec0bee8f02eb11d39ba12bfda6743e81750d81b01
3
+ size 1564661
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -402.3953315, "std_reward": 104.21036782376699, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-01T20:44:17.103054"}