Gueze commited on
Commit
bfb163f
1 Parent(s): 06ee2e4

Upload the first 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: 200.68 +/- 78.18
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 0x7f3c01079940>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3c010799d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3c01079a60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3c01079af0>", "_build": "<function ActorCriticPolicy._build at 0x7f3c01079b80>", "forward": "<function ActorCriticPolicy.forward at 0x7f3c01079c10>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3c01079ca0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3c01079d30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3c01079dc0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3c01079e50>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3c01079ee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f3c01072ae0>"}, "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": 524288, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670688689125169942, "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": -0.04857599999999995, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 160, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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_LunarGuezer.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:257b87da67165d2c3f5f127d718586a191e01f66fd8fd898f6051228c3f3bf65
3
+ size 147206
ppo_LunarGuezer/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.2
ppo_LunarGuezer/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 0x7f3c01079940>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3c010799d0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3c01079a60>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3c01079af0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f3c01079b80>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f3c01079c10>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3c01079ca0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f3c01079d30>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3c01079dc0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3c01079e50>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3c01079ee0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f3c01072ae0>"
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": 524288,
46
+ "_total_timesteps": 500000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1670688689125169942,
51
+ "learning_rate": 0.0003,
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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": -0.04857599999999995,
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": 160,
79
+ "n_steps": 2048,
80
+ "gamma": 0.99,
81
+ "gae_lambda": 0.95,
82
+ "ent_coef": 0.0,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 10,
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_LunarGuezer/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2f877660d099bdc3d1d007789c95d31681d08c03571a52db7bd6cdb58816d5dc
3
+ size 87929
ppo_LunarGuezer/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:08f9b98f773b38edc8db1d2cf91895d4605105cf41fab3db75597965635e7f85
3
+ size 43201
ppo_LunarGuezer/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_LunarGuezer/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 (236 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 200.68271637135368, "std_reward": 78.1768234850473, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-10T16:36:01.863820"}