Yuseifer commited on
Commit
57dc2c3
·
verified ·
1 Parent(s): a87a74f

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: 208.57 +/- 81.73
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 0x7c1fc91f2050>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c1fc91f20e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c1fc91f2170>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c1fc91f2200>", "_build": "<function ActorCriticPolicy._build at 0x7c1fc91f2290>", "forward": "<function ActorCriticPolicy.forward at 0x7c1fc91f2320>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c1fc91f23b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c1fc91f2440>", "_predict": "<function ActorCriticPolicy._predict at 0x7c1fc91f24d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c1fc91f2560>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c1fc91f25f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c1fc91f2680>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c1fc9387680>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1716252669679222504, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAMXmAb97dgE/vCsEPiVVfL6eH4e9Grr1uwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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 Sun Apr 28 14:29:16 UTC 2024", "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:be161caae38ec031a55beb52cc7a8a761026385526ca41076e48486004371237
3
+ size 147426
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 0x7c1fc91f2050>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c1fc91f20e0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c1fc91f2170>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c1fc91f2200>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7c1fc91f2290>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7c1fc91f2320>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c1fc91f23b0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c1fc91f2440>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7c1fc91f24d0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c1fc91f2560>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c1fc91f25f0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c1fc91f2680>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7c1fc9387680>"
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": 1716252669679222504,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAMXmAb97dgE/vCsEPiVVfL6eH4e9Grr1uwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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 sha256:4eb39d984b4f56985c021f0767d24566c2e9544052e0968b975c4ee7bac55e2b
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:f9ad4533a83bdb6191e498e74131db4e7aa9ee7c14f51332da2aa04606b2086f
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 Sun Apr 28 14:29:16 UTC 2024
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 (202 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 208.57021879999996, "std_reward": 81.72955890368185, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-21T01:43:41.677928"}