marmeladenaal commited on
Commit
897c0b6
1 Parent(s): c11a989

initial lunar lander

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: 285.78 +/- 16.61
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 0x7f15c65900d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f15c6590160>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f15c65901f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f15c6590280>", "_build": "<function ActorCriticPolicy._build at 0x7f15c6590310>", "forward": "<function ActorCriticPolicy.forward at 0x7f15c65903a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f15c6590430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f15c65904c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f15c6590550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f15c65905e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f15c6590670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f15c6590700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f15c6535880>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1712240057116411735, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_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": 380, "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": 16, "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-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:db7ec152c407645902d4638c8bb1aabf12c218e41e2afd2a1c0aa45f624c879b
3
+ size 147959
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 0x7f15c65900d0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f15c6590160>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f15c65901f0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f15c6590280>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f15c6590310>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f15c65903a0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f15c6590430>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f15c65904c0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f15c6590550>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f15c65905e0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f15c6590670>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f15c6590700>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f15c6535880>"
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": 1712240057116411735,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAKafsD0FQpw/7JgGP6ZDL79dHbY9yZKgPgAAAAAAAAAAzcnCvYS1pj+iz0W+E583v8AG6L0/T5u9AAAAAAAAAACg9ia+vy6ePzUZJ7+jwxS/ixRTvnJtmr4AAAAAAAAAAECJnT58ahs/2vPOPMPQCb9Xlc0+gVcwvgAAAAAAAAAAM9uuPLO4uz+2mIE9QZOXvs65ETwkKqY9AAAAAAAAAABtKx8+j4NZvCWIhDvgOqK5ITDDvTl7sLoAAIA/AACAP5pUgT3jng89c6SdvbU4X74UcJM83pdIvQAAAAAAAAAAM7hXvRSazbo9B38+Zws6PNmmB7srPSU9AAAAAAAAgD9zioo9j1ZMO8Uvib1slVe+Gr8bvWTnKbsAAAAAAAAAACbxoL3djok+ngY5Pmm1qr7u7R296tKaPQAAAAAAAAAAulo/vtcHCLtqNp0+06cEva9epLzaqkQ8AACAPwAAgD8ahti99tBcuqrfRT7hT7i07+Gku7V/j7MAAIA/AAAAAMaImL7O6a4+iHNuPvvH875hNjK+p0sMPgAAAAAAAAAAegUSvn0BFT5AZVI+tK6Evhi/5zxejKY9AAAAAAAAAADN1GU99oABulMi/L3TTQq06+XXO6eguTMAAIA/AACAPy2xV75pzTs/zVP4vSWaEb8oEGu+JmaKPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.015808000000000044,
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": 380,
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": 16,
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:f06b376849144ef847e32dcbd7972733ac89739ce289bfcc86cc65660d1cdd39
3
+ size 88362
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:72ecdbb381643162030ec23ac17f90f11a2c1027572c7071df7f016e9f6a93ba
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 (176 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 285.77719089999994, "std_reward": 16.607003006041065, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-04T14:52:02.301610"}