dasaprakashk commited on
Commit
b2d79fd
·
1 Parent(s): 1228f34

Upload PPO unarLander 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: 260.44 +/- 22.57
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 0x7f94001e4a60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f94001e4af0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f94001e4b80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f94001e4c10>", "_build": "<function ActorCriticPolicy._build at 0x7f94001e4ca0>", "forward": "<function ActorCriticPolicy.forward at 0x7f94001e4d30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f94001e4dc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f94001e4e50>", "_predict": "<function ActorCriticPolicy._predict at 0x7f94001e4ee0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f94001e4f70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f94001e7040>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f94001e70d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f94001dda80>"}, "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": 1673468256358867258, "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-glibc2.27 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+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:ed74bcfa5add70c21203caed518d6effcd3683af80d82e82e0d1edd9f6b3319c
3
+ size 147408
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
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 0x7f94001e4a60>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f94001e4af0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f94001e4b80>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f94001e4c10>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f94001e4ca0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f94001e4d30>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f94001e4dc0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f94001e4e50>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f94001e4ee0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f94001e4f70>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f94001e7040>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f94001e70d0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7f94001dda80>"
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": 1673468256358867258,
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": -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:": "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"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null
95
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:11d363adf7eb048098d1fd6746fb0ed5733012ecc2dc828c68b4f6818c7fc81c
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4d68757a98a1799af36c7650900ca307c1781acbca099bea980cc3cddef1bc41
3
+ size 43393
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-5.10.147+-x86_64-with-glibc2.27 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.16
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.21.6
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (213 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 260.4436414544214, "std_reward": 22.56853272043707, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-11T20:40:43.639236"}