Augcos commited on
Commit
c8fce21
·
1 Parent(s): 29c56d0

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: 262.76 +/- 22.28
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 0x7f0bc592fd30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0bc592fdc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0bc592fe50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0bc592fee0>", "_build": "<function ActorCriticPolicy._build at 0x7f0bc592ff70>", "forward": "<function ActorCriticPolicy.forward at 0x7f0bc5935040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0bc59350d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0bc5935160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0bc59351f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0bc5935280>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0bc5935310>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0bc5931240>"}, "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": 1672054307396193075, "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 sha256:0ad9565eb4a5c34aeeb3093a87d6e300e0d50cb8b9cdae65f139d20094dd8883
3
+ size 147218
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 0x7f0bc592fd30>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0bc592fdc0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0bc592fe50>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0bc592fee0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f0bc592ff70>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f0bc5935040>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0bc59350d0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f0bc5935160>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0bc59351f0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0bc5935280>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0bc5935310>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f0bc5931240>"
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": 1672054307396193075,
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:bf54b39712295394110111db955f04a35a28e006cf53017a1426a12aad02b11f
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:da53b203c8a004eb1a3f0acc15b5f7e2171eb24ec6e9113f7fd6158d65fd1d8e
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 (241 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 262.7584911492108, "std_reward": 22.276778673128376, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-26T11:53:31.974487"}