xavidejuan commited on
Commit
e71679e
·
1 Parent(s): ed16f8c

Upload PPO LunarLander-v2 trained agent

Browse files
README.md CHANGED
@@ -1,3 +1,37 @@
1
  ---
2
- license: gpl-3.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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: 219.97 +/- 70.93
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 0x7f9d32710160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9d327101f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9d32710280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9d32710310>", "_build": "<function ActorCriticPolicy._build at 0x7f9d327103a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f9d32710430>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9d327104c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9d32710550>", "_predict": "<function ActorCriticPolicy._predict at 0x7f9d327105e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9d32710670>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9d32710700>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9d32710790>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f9d32711540>"}, "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": 1679253210472340985, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAACA4fb42WAc90obLuktJrTmt3pq+a50iOgAAAAAAAIA/ZlCTPC58/T3j+vY8rBUhvkoYrbqSY5G7AAAAAAAAAAANYz6+/DriPuIy4j0Oc0y+owJMvPv1izwAAAAAAAAAAObhXr2umYy6MrEdOQ3qmDTynUA7ifQzuAAAgD8AAIA/zajGveyBmLl4Geu6dwIPtm+7gjvycgo6AACAPwAAgD/NCMM7HwXMOEPZYrqmowO2mwgcPLpgiTkAAIA/AACAP5opujzHxC8+ey+PvebmUL7SiH28ttRdPQAAAAAAAAAAjTK0PcPJbrpQ0de6mzAIOOzga7plaWg5AACAPwAAAACzLg49w91IuvZahrtlLPS0bF1suxo9SzQAAIA/AACAP2aCDD2kgA+5CvqnuzUamrZnJVy7wk/GOgAAgD8AAIA/gLxJvUjphborT2I67y5gNdzw57q1f4O5AACAPwAAgD/mnFM9XOtlulIYqDTVPe4uyTH6uVi9UbMAAIA/AACAPwBQnzvs6e25hP6/uldRADhHve85/u5ROQAAgD8AAIA/ADIaPSlYFrqqjY+5sg7dtNoS0TuFyak4AACAPwAAgD+6chi+9sNOvBYkqjrMUMk4yeWtPdDL5rkAAIA/AACAP2ambbzh2IS6tvcWPHMSHbYedcG6PdsUtQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
ppo_lunarlander-v2_first-try.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f42a75352127b419a80faaa56a314e0cdfe808619b7f7921272e7cf891ed6a17
3
+ size 147425
ppo_lunarlander-v2_first-try/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
ppo_lunarlander-v2_first-try/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 0x7f9d32710160>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9d327101f0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9d32710280>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9d32710310>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f9d327103a0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f9d32710430>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9d327104c0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9d32710550>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f9d327105e0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9d32710670>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9d32710700>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9d32710790>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f9d32711540>"
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": 1679253210472340985,
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_first-try/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c3c05cae7fefed6ba433f799816e01448beaaff48d877e60af9c5ec88b899d9d
3
+ size 87929
ppo_lunarlander-v2_first-try/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e67998a7a130d037d47ae9cf424152e742b13654debb35bf45e97ad1f4e4fd7e
3
+ size 43393
ppo_lunarlander-v2_first-try/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_first-try/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.9.16
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (223 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 219.96556724441544, "std_reward": 70.93097185983238, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-19T19:37:26.811638"}