JacksonBurton commited on
Commit
3b0358a
1 Parent(s): c560682

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: 226.79 +/- 24.77
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 0x7fc2e6cb0c10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc2e6cb0ca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc2e6cb0d30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc2e6cb0dc0>", "_build": "<function ActorCriticPolicy._build at 0x7fc2e6cb0e50>", "forward": "<function ActorCriticPolicy.forward at 0x7fc2e6cb0ee0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc2e6cb0f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc2e6cb1000>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc2e6cb1090>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc2e6cb1120>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc2e6cb11b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc2e6cb1240>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fc2e6cadc80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1682975453027135647, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAAASrTz27Cu60sFsuW8dkDTeuIc5Rq3xswAAgD8AAIA/ZqYuu7DpPD+uFxk9nEV9vmCaE709v/A7AAAAAAAAAAAAYqe8KTBcurfcjjxc4a04oe+Vus1oqjcAAIA/AACAP2Y8tryPwm66iHirO6XCKThSPO06Fs8gtwAAgD8AAIA/zV1MveEQmLoIfbc7rSFkOLWYrDoAKPC3AACAPwAAgD8AK3w9KVAhutbvfLr+sbu1GbFNuwCwkjkAAIA/AACAPzNa2DyUZq4/ZzInP0GXC79VEwi9YtMbvgAAAAAAAAAAoMxxvotZRz8CiOI9PPk4vrWAZ71kWjO9AAAAAAAAAAAmKBG+7SeeP43SHr+0QbK+O/eMvdNoPb4AAAAAAAAAAM3k0zx7upG6QrHfuv7VCbZWI8o6fJoBOgAAgD8AAIA/MzuZPCNyrT/LA3Y+74OOvtJW+Lv9KcM8AAAAAAAAAADmrWo94cSAunsoQrk3QDS0+guBug6vYjgAAIA/AACAPyYrYj57ajw/zcj6vYQOS76+5wc8vYBcPAAAAAAAAAAAALq+PaSAQrnCmQ289+kEN8NKjDvGFn62AAAAAAAAgD+ADCs9UpjPud7Zd7rkWBm2k4oIvCk4lTkAAIA/AACAPxogYD2/Svs+mBXeveADZL7NipW9EKfGvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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, "_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": 248, "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": "3.10.11", "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:dfc388423c3fb3fdbd6b232ae473ac9b0af932be6c65c7bf03e9cb4df6f33fc9
3
+ size 147396
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 0x7fc2e6cb0c10>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc2e6cb0ca0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc2e6cb0d30>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc2e6cb0dc0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fc2e6cb0e50>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fc2e6cb0ee0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc2e6cb0f70>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc2e6cb1000>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fc2e6cb1090>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc2e6cb1120>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc2e6cb11b0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc2e6cb1240>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7fc2e6cadc80>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1015808,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1682975453027135647,
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": -0.015808000000000044,
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": 248,
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:d552085ebadfb109f79dbd26a078ed01cba56a7d0f7adc97a10a41352db03eac
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:60219df503064bd440e84263e3b930e15787f24a2310d2fd1fc3199f76f3ac83
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: 3.10.11
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 (222 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 226.79349457240886, "std_reward": 24.773105846047688, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-01T21:38:54.486842"}