tushar117 commited on
Commit
2a2b5b3
1 Parent(s): d9d68e4

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: 262.95 +/- 13.99
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 0x7f8435df9040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8435df90d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8435df9160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8435df91f0>", "_build": "<function ActorCriticPolicy._build at 0x7f8435df9280>", "forward": "<function ActorCriticPolicy.forward at 0x7f8435df9310>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8435df93a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8435df9430>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8435df94c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8435df9550>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8435df95e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f8435df08d0>"}, "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": 1672664839390291322, "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-5.10.133+-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:d5b36b82def3d2df090e484894910b70af0ea06457b2ffc3fc8cf1c8db4305aa
3
+ size 147210
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 0x7f8435df9040>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8435df90d0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8435df9160>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8435df91f0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f8435df9280>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f8435df9310>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8435df93a0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f8435df9430>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8435df94c0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8435df9550>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8435df95e0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f8435df08d0>"
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": 1672664839390291322,
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:": "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:e0450bd0bc981d9ea9648db127d13cb15748f7e903fcb11c0edb648f178d278a
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6348fc2a01c1bc153d498cd3b96f202f69a25979a6ff4ea00e1e9dc16702f489
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 (250 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 262.95314347017234, "std_reward": 13.987471806210843, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-02T13:50:40.611719"}