zgerem commited on
Commit
f1a869a
·
verified ·
1 Parent(s): d3730c6

Upload PPO LunarLander-v2 trained agen

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ replay.mp4 filter=lfs diff=lfs merge=lfs -text
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: 272.34 +/- 18.18
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 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 0x7d488b500fe0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d488b501080>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d488b501120>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d488b5011c0>", "_build": "<function ActorCriticPolicy._build at 0x7d488b501260>", "forward": "<function ActorCriticPolicy.forward at 0x7d488b501300>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d488b5013a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d488b501440>", "_predict": "<function ActorCriticPolicy._predict at 0x7d488b5014e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d488b501580>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d488b501620>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d488b5016c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d488b679ec0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1740097227181037875, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": null, "_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 '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:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "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 sha256:6089eaaae47a2d1ba767158b2b22d7eecd79089daaca601d9d181ddaceb63e81
3
+ size 147364
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 0x7d488b500fe0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d488b501080>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d488b501120>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d488b5011c0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7d488b501260>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7d488b501300>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d488b5013a0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d488b501440>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7d488b5014e0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d488b501580>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d488b501620>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d488b5016c0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7d488b679ec0>"
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": 1740097227181037875,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": null,
33
+ "_last_episode_starts": {
34
+ ":type:": "<class 'numpy.ndarray'>",
35
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
36
+ },
37
+ "_last_original_obs": null,
38
+ "_episode_num": 0,
39
+ "use_sde": false,
40
+ "sde_sample_freq": -1,
41
+ "_current_progress_remaining": -0.015808000000000044,
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": 248,
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:b2e4caa4f0bd4e7620fb4e66cb6f73e56626fc32c6478e1318fc7bcc4b6232f7
3
+ size 88490
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:299c227e35627bc4c45283e6e18a6650dbca10fdd78f30deebaec0dba3bf4527
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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
2
+ - Python: 3.11.11
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.5.1+cu124
5
+ - GPU Enabled: True
6
+ - Numpy: 1.26.4
7
+ - Cloudpickle: 3.1.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:87b76ca10666378fcb9cdb351baff4cc53d6db02f20dc12574eaaf62e2d09773
3
+ size 164633
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 272.3395799, "std_reward": 18.182766379769948, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-02-21T00:40:54.110005"}