MontaR commited on
Commit
eae2e1e
1 Parent(s): 5a44327

init LL-v2

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: 276.78 +/- 18.42
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7fbc84a58310>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbc84a583a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbc84a58430>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbc84a584c0>", "_build": "<function ActorCriticPolicy._build at 0x7fbc84a58550>", "forward": "<function ActorCriticPolicy.forward at 0x7fbc84a585e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbc84a58670>", "_predict": "<function ActorCriticPolicy._predict at 0x7fbc84a58700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbc84a58790>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbc84a58820>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbc84a588b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fbc84a4f900>"}, "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": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670577043148219878, "learning_rate": 0.0001, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEAAAAAAAAAAQAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 992, "n_steps": 2048, "gamma": 0.999999, "gae_lambda": 0.99, "ent_coef": 0.0001, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 16, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:16d635f930e9993634b5bde8b9317ed40eb7be59fc5e1172945b83c367b25f65
3
+ size 147196
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.2
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7fbc84a58310>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbc84a583a0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbc84a58430>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbc84a584c0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fbc84a58550>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fbc84a585e0>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbc84a58670>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fbc84a58700>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbc84a58790>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbc84a58820>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbc84a588b0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fbc84a4f900>"
20
+ },
21
+ "verbose": 1,
22
+ "policy_kwargs": {},
23
+ "observation_space": {
24
+ ":type:": "<class 'gym.spaces.box.Box'>",
25
+ ":serialized:": "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",
26
+ "dtype": "float32",
27
+ "_shape": [
28
+ 8
29
+ ],
30
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
31
+ "high": "[inf inf inf inf inf inf inf inf]",
32
+ "bounded_below": "[False False False False False False False False]",
33
+ "bounded_above": "[False False False False False False False False]",
34
+ "_np_random": null
35
+ },
36
+ "action_space": {
37
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
38
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 16,
45
+ "num_timesteps": 2031616,
46
+ "_total_timesteps": 2000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1670577043148219878,
51
+ "learning_rate": 0.0001,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "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"
56
+ },
57
+ "_last_obs": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "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"
60
+ },
61
+ "_last_episode_starts": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEAAAAAAAAAAQAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
64
+ },
65
+ "_last_original_obs": null,
66
+ "_episode_num": 0,
67
+ "use_sde": false,
68
+ "sde_sample_freq": -1,
69
+ "_current_progress_remaining": -0.015808000000000044,
70
+ "ep_info_buffer": {
71
+ ":type:": "<class 'collections.deque'>",
72
+ ":serialized:": "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"
73
+ },
74
+ "ep_success_buffer": {
75
+ ":type:": "<class 'collections.deque'>",
76
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 992,
79
+ "n_steps": 2048,
80
+ "gamma": 0.999999,
81
+ "gae_lambda": 0.99,
82
+ "ent_coef": 0.0001,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 16,
87
+ "clip_range": {
88
+ ":type:": "<class 'function'>",
89
+ ":serialized:": "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"
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9ebc5d8f7d6de3eefa2cf8743b3adf56ae08c71c00c1a059ffe975dffe3d0db4
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:d5376ce8ea001d6c32d082d6fe409260a4ff836340ddfead8b4e69575a5734c7
3
+ size 43201
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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
2
+ Python: 3.8.16
3
+ Stable-Baselines3: 1.6.2
4
+ PyTorch: 1.13.0+cu116
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
Binary file (211 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 276.78137727371745, "std_reward": 18.422383302269107, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-09T10:18:23.376504"}