tringuyexn commited on
Commit
cb43ea0
1 Parent(s): a403bad

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: 237.09 +/- 23.08
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 0x7fb174f4bf80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb174ed3050>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb174ed30e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb174ed3170>", "_build": "<function ActorCriticPolicy._build at 0x7fb174ed3200>", "forward": "<function ActorCriticPolicy.forward at 0x7fb174ed3290>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb174ed3320>", "_predict": "<function ActorCriticPolicy._predict at 0x7fb174ed33b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb174ed3440>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb174ed34d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb174ed3560>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fb174f2b0f0>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1666281260897521148, "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": 124, "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-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+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:af375ceea9a49dedc87a5c97969fa66d19c0560a70de34cceb880cb4f8205a24
3
+ size 147150
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 0x7fb174f4bf80>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb174ed3050>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb174ed30e0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb174ed3170>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fb174ed3200>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fb174ed3290>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb174ed3320>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fb174ed33b0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb174ed3440>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb174ed34d0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb174ed3560>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fb174f2b0f0>"
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": 507904,
46
+ "_total_timesteps": 500000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1666281260897521148,
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:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAALPXCz2FI7W5mgouOlFP0DSu45K73Z1MuQAAgD8AAIA/wGmTPbhew7nS4D48jUUROXSi+7oz1xE4AACAPwAAgD+tdnU+o88eP+OYjb1jfJC+P7XEPQLVOL0AAAAAAAAAAM3OGr0UvI26J2qju1loAjihdxA6XfpfOgAAgD8AAIA/TUgrvY/eQLqINpi7Oacqs6HO6zlSTV8zAACAPwAAgD+a/hS9j+Y+upUBpTz+ikA3diVuuc6AODYAAIA/AACAP2aOrjvsObm5WzfquilatrUc4KK6+xoIOgAAgD8AAIA/c0KzvY8eIrpc6D05qaUdNGAo+bmuhle4AACAPwAAgD8AW3y9CSipPv10qz0u0GK+07n1vDk2mz0AAAAAAAAAAAB/4D0pTFi6Kp9SORp36DWGUIE7SKpyuAAAgD8AAIA/mnn7O1ynZ7rIygG8v2w5NeMF+Dp+j6S0AACAPwAAgD+T8A4+SCGRO7S6SDl3Zbw2w985Pc+og7gAAIA/AACAP82kpzzDzSi6+YqpO0Bh3rWFgAY7oLbVtAAAgD8AAIA/WlWDPkXYmDwtSSg40KWONsxYIj5K7lG3AACAPwAAgD9zp0I+fWUUPLzNHrxn8A66VaChPTiTBrsAAIA/AACAPxreOz3DiXi6ms8DOxp0ZDeLoj0586lVNgAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
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": 124,
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:ccbeeedcec9a7cda6e8305205ec233bbdde277f99ea35a9286e38a26ae4b2036
3
+ size 87865
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3e255c08b0c857c2faef273dea3638b603bcec7c9cd55ea294b7ea0ae68938c8
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-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022
2
+ Python: 3.7.15
3
+ Stable-Baselines3: 1.6.2
4
+ PyTorch: 1.12.1+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
Binary file (247 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 237.09387966890077, "std_reward": 23.083019581506182, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-20T16:55:34.102007"}