ikorennoy commited on
Commit
9b3b9ac
1 Parent(s): 4f96703

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: 285.31 +/- 16.22
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 0x7e0cd0c8cca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e0cd0c8cd30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e0cd0c8cdc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e0cd0c8ce50>", "_build": "<function ActorCriticPolicy._build at 0x7e0cd0c8cee0>", "forward": "<function ActorCriticPolicy.forward at 0x7e0cd0c8cf70>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e0cd0c8d000>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e0cd0c8d090>", "_predict": "<function ActorCriticPolicy._predict at 0x7e0cd0c8d120>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e0cd0c8d1b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e0cd0c8d240>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e0cd0c8d2d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e0cd0c26c80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713820334437965338, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAABOND3heIS69bjmtkuk3rFdmV06RwkHNgAAgD8AAIA/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": 4344, "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:a2ffe919cd6bdc8f8b095aac8e5f6acf1e5d1b285f293c948ced72ba262219c3
3
+ size 147518
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 0x7e0cd0c8cca0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e0cd0c8cd30>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e0cd0c8cdc0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e0cd0c8ce50>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7e0cd0c8cee0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7e0cd0c8cf70>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e0cd0c8d000>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e0cd0c8d090>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7e0cd0c8d120>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e0cd0c8d1b0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e0cd0c8d240>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e0cd0c8d2d0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7e0cd0c26c80>"
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": 1713820334437965338,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAABOND3heIS69bjmtkuk3rFdmV06RwkHNgAAgD8AAIA/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": 4344,
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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
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:affd3a7c8473a107a14097f311d7d888c0d83304f60fe811bec6cd06ed86fe3f
3
+ size 88490
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:67308c67a2f3191ced5481940351b8e9b98c83919f3dac9d4c3c08013646954b
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 (170 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 285.3095796, "std_reward": 16.22441621155832, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-22T21:49:00.663785"}