tro8 commited on
Commit
a939af6
1 Parent(s): 2eef517
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: MlpPolicy
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: 251.35 +/- 19.22
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **MlpPolicy** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **MlpPolicy** 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 0x787cf16de4d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x787cf16de560>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x787cf16de5f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x787cf16de680>", "_build": "<function ActorCriticPolicy._build at 0x787cf16de710>", "forward": "<function ActorCriticPolicy.forward at 0x787cf16de7a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x787cf16de830>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x787cf16de8c0>", "_predict": "<function ActorCriticPolicy._predict at 0x787cf16de950>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x787cf16de9e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x787cf16dea70>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x787cf16deb00>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x787cf1679fc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711464766607530041, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": null, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3908, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d4df9bca5ac230d116bdcedbfef8d3c22b4ed7606b486a26a152a82770ba218c
3
+ size 147283
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
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 0x787cf16de4d0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x787cf16de560>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x787cf16de5f0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x787cf16de680>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x787cf16de710>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x787cf16de7a0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x787cf16de830>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x787cf16de8c0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x787cf16de950>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x787cf16de9e0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x787cf16dea70>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x787cf16deb00>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x787cf1679fc0>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1000448,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1711464766607530041,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": null,
33
+ "_last_episode_starts": {
34
+ ":type:": "<class 'numpy.ndarray'>",
35
+ ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
36
+ },
37
+ "_last_original_obs": null,
38
+ "_episode_num": 0,
39
+ "use_sde": false,
40
+ "sde_sample_freq": -1,
41
+ "_current_progress_remaining": -0.00044800000000000395,
42
+ "_stats_window_size": 100,
43
+ "ep_info_buffer": {
44
+ ":type:": "<class 'collections.deque'>",
45
+ ":serialized:": "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"
46
+ },
47
+ "ep_success_buffer": {
48
+ ":type:": "<class 'collections.deque'>",
49
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
50
+ },
51
+ "_n_updates": 3908,
52
+ "observation_space": {
53
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
54
+ ":serialized:": "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",
55
+ "dtype": "float32",
56
+ "bounded_below": "[ True True True True True True True True]",
57
+ "bounded_above": "[ True True True True True True True True]",
58
+ "_shape": [
59
+ 8
60
+ ],
61
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
62
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
63
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
64
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
65
+ "_np_random": null
66
+ },
67
+ "action_space": {
68
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
69
+ ":serialized:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
70
+ "n": "4",
71
+ "start": "0",
72
+ "_shape": [],
73
+ "dtype": "int64",
74
+ "_np_random": null
75
+ },
76
+ "n_envs": 1,
77
+ "n_steps": 1024,
78
+ "gamma": 0.999,
79
+ "gae_lambda": 0.98,
80
+ "ent_coef": 0.01,
81
+ "vf_coef": 0.5,
82
+ "max_grad_norm": 0.5,
83
+ "batch_size": 64,
84
+ "n_epochs": 4,
85
+ "clip_range": {
86
+ ":type:": "<class 'function'>",
87
+ ":serialized:": "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"
88
+ },
89
+ "clip_range_vf": null,
90
+ "normalize_advantage": true,
91
+ "target_kl": null,
92
+ "lr_schedule": {
93
+ ":type:": "<class 'function'>",
94
+ ":serialized:": "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"
95
+ }
96
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:de6e96ec4f59efd52ce4d890adb204b2f792ce8cb798c2ae0b303b3f4aa3203a
3
+ size 88490
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:01b6371005c93643ff9036235242f2347cbb160112cf6402f864e6e409208f8b
3
+ size 43762
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
3
+ size 864
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.2.1+cu121
5
+ - GPU Enabled: True
6
+ - Numpy: 1.25.2
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (191 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 251.35179680000002, "std_reward": 19.215396123988665, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-26T15:59:11.271441"}