sal-ops commited on
Commit
92f8225
·
1 Parent(s): f0ad72c

Upload PPO LunarLander-v2 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: 191.03 +/- 67.93
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 0x7e9701a767a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e9701a76830>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e9701a768c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e9701a76950>", "_build": "<function ActorCriticPolicy._build at 0x7e9701a769e0>", "forward": "<function ActorCriticPolicy.forward at 0x7e9701a76a70>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e9701a76b00>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e9701a76b90>", "_predict": "<function ActorCriticPolicy._predict at 0x7e9701a76c20>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e9701a76cb0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e9701a76d40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e9701a76dd0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e9701a11100>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1001472, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1699488211907818776, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAKA4Ir6Cpq4/5swIvxATi758V4y9tModvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.0014719999999999178, "_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": 9780, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "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 sha256:0a046131709f45db896c15b877891c2f2a06e278b1444868584b4f466ec99ef3
3
+ size 147394
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 0x7e9701a767a0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e9701a76830>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e9701a768c0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e9701a76950>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7e9701a769e0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7e9701a76a70>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e9701a76b00>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e9701a76b90>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7e9701a76c20>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e9701a76cb0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e9701a76d40>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e9701a76dd0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7e9701a11100>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1001472,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1699488211907818776,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAKA4Ir6Cpq4/5swIvxATi758V4y9tModvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.0014719999999999178,
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": 9780,
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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
73
+ "n": "4",
74
+ "start": "0",
75
+ "_shape": [],
76
+ "dtype": "int64",
77
+ "_np_random": null
78
+ },
79
+ "n_envs": 1,
80
+ "n_steps": 2048,
81
+ "gamma": 0.99,
82
+ "gae_lambda": 0.95,
83
+ "ent_coef": 0.0,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 10,
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:f932c34a17745d1e98c1e413c35c106d6dd3a2d542b70f6a92b54490e25c36d1
3
+ size 88362
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:888b0a7ff053dd375886dc5a75eef41eaa3ce9d495bb915c34e768f69a6243a7
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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.1.0+cu118
5
+ - GPU Enabled: True
6
+ - Numpy: 1.23.5
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (163 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 191.03225859516436, "std_reward": 67.92574819246079, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-09T00:58:16.936878"}