SMD1234 commited on
Commit
0a90acc
1 Parent(s): 90fcba5

Push Lunar Lander-v2 model

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: 281.74 +/- 17.96
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 0x7faa2e2e6ca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7faa2e2e6d30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7faa2e2e6dc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7faa2e2e6e50>", "_build": "<function ActorCriticPolicy._build at 0x7faa2e2e6ee0>", "forward": "<function ActorCriticPolicy.forward at 0x7faa2e2e6f70>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7faa2e2ea040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7faa2e2ea0d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7faa2e2ea160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7faa2e2ea1f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7faa2e2ea280>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7faa2e2ea310>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7faa2e2e7f80>"}, "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": 1501440, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1680637138033169097, "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": -0.0009600000000000719, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3680, "n_steps": 102, "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": "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 sha256:9d584e5d65cab9e397f087ded30262e6ed62bea4c8ad151711ca221eaeaf7ab2
3
+ size 147345
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 0x7faa2e2e6ca0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7faa2e2e6d30>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7faa2e2e6dc0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7faa2e2e6e50>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7faa2e2e6ee0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7faa2e2e6f70>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7faa2e2ea040>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7faa2e2ea0d0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7faa2e2ea160>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7faa2e2ea1f0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7faa2e2ea280>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7faa2e2ea310>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7faa2e2e7f80>"
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": 1501440,
47
+ "_total_timesteps": 1500000,
48
+ "_num_timesteps_at_start": 0,
49
+ "seed": null,
50
+ "action_noise": null,
51
+ "start_time": 1680637138033169097,
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": -0.0009600000000000719,
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": 3680,
80
+ "n_steps": 102,
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:f74f473510aad731c63ca95839b301459a68c2907cb77fe7d1bcd24e054ab538
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:e84951a3feeaa21e075d5fc0fdc070338682f96b875820a4674bd556f36cd851
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: 2.0.0+cu118
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (195 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 281.7369339633834, "std_reward": 17.96211471858424, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-04T20:08:32.344066"}