HilbertS commited on
Commit
9cb6f2a
1 Parent(s): 910bda8

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: -162.60 +/- 105.38
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 0x7fd8618fc3a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd8618fc430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd8618fc4c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd8618fc550>", "_build": "<function ActorCriticPolicy._build at 0x7fd8618fc5e0>", "forward": "<function ActorCriticPolicy.forward at 0x7fd8618fc670>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd8618fc700>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd8618fc790>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd8618fc820>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd8618fc8b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd8618fc940>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd8618fc9d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd8618fe100>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 16384, "_total_timesteps": 10000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1682355569098482710, "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": -0.6384000000000001, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 4, "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, "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": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "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:c8a8b75a04b3f59447306c6ffcf4391e4a26bc2c5562d34c7e2f8b0c1e0e852f
3
+ size 147255
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.8.0
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,96 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7fd8618fc3a0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd8618fc430>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd8618fc4c0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd8618fc550>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fd8618fc5e0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fd8618fc670>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd8618fc700>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd8618fc790>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fd8618fc820>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd8618fc8b0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd8618fc940>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd8618fc9d0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7fd8618fe100>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 16384,
25
+ "_total_timesteps": 10000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1682355569098482710,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "lr_schedule": {
33
+ ":type:": "<class 'function'>",
34
+ ":serialized:": "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"
35
+ },
36
+ "_last_obs": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "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"
39
+ },
40
+ "_last_episode_starts": {
41
+ ":type:": "<class 'numpy.ndarray'>",
42
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
43
+ },
44
+ "_last_original_obs": null,
45
+ "_episode_num": 0,
46
+ "use_sde": false,
47
+ "sde_sample_freq": -1,
48
+ "_current_progress_remaining": -0.6384000000000001,
49
+ "_stats_window_size": 100,
50
+ "ep_info_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "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"
53
+ },
54
+ "ep_success_buffer": {
55
+ ":type:": "<class 'collections.deque'>",
56
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
57
+ },
58
+ "_n_updates": 4,
59
+ "observation_space": {
60
+ ":type:": "<class 'gym.spaces.box.Box'>",
61
+ ":serialized:": "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",
62
+ "dtype": "float32",
63
+ "_shape": [
64
+ 8
65
+ ],
66
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
67
+ "high": "[inf inf inf inf inf inf inf inf]",
68
+ "bounded_below": "[False False False False False False False False]",
69
+ "bounded_above": "[False False False False False False False False]",
70
+ "_np_random": null
71
+ },
72
+ "action_space": {
73
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
74
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
75
+ "n": 4,
76
+ "_shape": [],
77
+ "dtype": "int64",
78
+ "_np_random": null
79
+ },
80
+ "n_envs": 16,
81
+ "n_steps": 1024,
82
+ "gamma": 0.999,
83
+ "gae_lambda": 0.98,
84
+ "ent_coef": 0.01,
85
+ "vf_coef": 0.5,
86
+ "max_grad_norm": 0.5,
87
+ "batch_size": 64,
88
+ "n_epochs": 4,
89
+ "clip_range": {
90
+ ":type:": "<class 'function'>",
91
+ ":serialized:": "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"
92
+ },
93
+ "clip_range_vf": null,
94
+ "normalize_advantage": true,
95
+ "target_kl": null
96
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2031faa371e9978e9e4824a49080f48de67d107a197b803e7bb02d19dcfc3db4
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:135486318a18074f515bdec8aeec19fba6e3028e00c0745ff97c93bb8eadf6fe
3
+ size 43329
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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.9.16
3
+ - Stable-Baselines3: 1.8.0
4
+ - PyTorch: 2.0.0+cu118
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (243 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -162.60268556866794, "std_reward": 105.37861394937612, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-24T17:00:26.720540"}