astefani commited on
Commit
fdffedd
·
1 Parent(s): 93fda0b

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: 262.09 +/- 23.48
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 0x7fc52ddc43a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc52ddc4430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc52ddc44c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc52ddc4550>", "_build": "<function ActorCriticPolicy._build at 0x7fc52ddc45e0>", "forward": "<function ActorCriticPolicy.forward at 0x7fc52ddc4670>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc52ddc4700>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc52ddc4790>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc52ddc4820>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc52ddc48b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc52ddc4940>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc52ddc49d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fc52ddc2d40>"}, "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": 1678972204769555264, "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-glibc2.31 # 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.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:31fa4caeaec71a1ede343de0f046039d6cf67951268426a8d604e8099439ebe5
3
+ size 147405
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 0x7fc52ddc43a0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc52ddc4430>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc52ddc44c0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc52ddc4550>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fc52ddc45e0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fc52ddc4670>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc52ddc4700>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc52ddc4790>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fc52ddc4820>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc52ddc48b0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc52ddc4940>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc52ddc49d0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7fc52ddc2d40>"
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": 1678972204769555264,
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 sha256:995b8cb4209b91acdda28f3f0863144f56077015d3e188f3373e1010f55bb4ef
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3659f7312b2e4d66257919c30d34d0df5b42818ea0c4b8065f2ec326e6ba2c79
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-glibc2.31 # 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 (236 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 262.0869796701735, "std_reward": 23.478927916093113, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-16T13:30:21.348231"}