Misbah ur rahman commited on
Commit
574e802
·
verified ·
1 Parent(s): 7e656f9

Upload PPO LunarLander-v2 trained agent

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: 273.88 +/- 18.19
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 0x7d00d953fec0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d00d953ff60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d00d954c040>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d00d954c0e0>", "_build": "<function ActorCriticPolicy._build at 0x7d00d954c180>", "forward": "<function ActorCriticPolicy.forward at 0x7d00d954c220>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d00d954c2c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d00d954c360>", "_predict": "<function ActorCriticPolicy._predict at 0x7d00d954c400>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d00d954c4a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d00d954c540>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d00d954c5e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d00d96b1600>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1742052177778333268, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAM1o9Ds2VxW82y6dPAAqjjxr9HU9zrNsvQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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": "2.6.0+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 sha256:31007356c8a47604ca4cd53662199823869760fd74a711fd67de6f7e34160275
3
+ size 147410
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7d00d953fec0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d00d953ff60>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d00d954c040>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d00d954c0e0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7d00d954c180>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7d00d954c220>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d00d954c2c0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d00d954c360>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7d00d954c400>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d00d954c4a0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d00d954c540>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d00d954c5e0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7d00d96b1600>"
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": 1742052177778333268,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAM1o9Ds2VxW82y6dPAAqjjxr9HU9zrNsvQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.00044800000000000395,
45
+ "_stats_window_size": 100,
46
+ "ep_info_buffer": {
47
+ ":type:": "<class 'collections.deque'>",
48
+ ":serialized:": "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"
49
+ },
50
+ "ep_success_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
53
+ },
54
+ "_n_updates": 3908,
55
+ "observation_space": {
56
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
+ ":serialized:": "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",
58
+ "dtype": "float32",
59
+ "bounded_below": "[ True True True True True True True True]",
60
+ "bounded_above": "[ True True True True True True True True]",
61
+ "_shape": [
62
+ 8
63
+ ],
64
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
65
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
66
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
67
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
68
+ "_np_random": null
69
+ },
70
+ "action_space": {
71
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
72
+ ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
73
+ "n": "4",
74
+ "start": "0",
75
+ "_shape": [],
76
+ "dtype": "int64",
77
+ "_np_random": null
78
+ },
79
+ "n_envs": 1,
80
+ "n_steps": 1024,
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
+ "lr_schedule": {
96
+ ":type:": "<class 'function'>",
97
+ ":serialized:": "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"
98
+ }
99
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8d682aeff3f87eb6b2bf3a4d0d1acb34833b65e57a8094835cbe666de20e3705
3
+ size 88362
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:146fe9bce25c66f862da9a2236e597691fa574dc6e348865aac41541ca45531f
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: 2.6.0+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:a802f8c5589e1af521f0a3b936b9d9f2954494ac6ff6f89168e02e847fd90fbd
3
+ size 164033
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 273.8802931345723, "std_reward": 18.1916165841282, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-03-15T16:07:10.671463"}