Hardwarize commited on
Commit
021b46a
1 Parent(s): 6595071

Initial commit

Browse files
README.md ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ - metrics:
12
+ - type: mean_reward
13
+ value: 228.17 +/- 17.10
14
+ name: mean_reward
15
+ task:
16
+ type: reinforcement-learning
17
+ name: reinforcement-learning
18
+ dataset:
19
+ name: LunarLander-v2
20
+ type: LunarLander-v2
21
+ ---
22
+
23
+ # **PPO** Agent playing **LunarLander-v2**
24
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
25
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
26
+
27
+ ## Usage (with Stable-baselines3)
28
+ TODO: Add your code
29
+
30
+
31
+ ```python
32
+ from stable_baselines3 import ...
33
+ from huggingface_sb3 import load_from_hub
34
+
35
+ ...
36
+ ```
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7ff0c2161440>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff0c21614d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff0c2161560>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff0c21615f0>", "_build": "<function ActorCriticPolicy._build at 0x7ff0c2161680>", "forward": "<function ActorCriticPolicy.forward at 0x7ff0c2161710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff0c21617a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff0c2161830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff0c21618c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff0c2161950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff0c21619e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff0c21b3300>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1661359363.7094195, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAOZZBT1cWzi6XvEtvOqNEzdnnNM5oNeItgAAgD8AAIA/mhlgusNxMLqS8KI6XsHDNbkaYTpyi7i5AACAPwAAgD9mNpI9hUuWuTV8iTuiNeM20YSFOwNg2TUAAIA/AACAP6b05j2uR6u6i7mHvLKOtrpbVXQ7AmWKuwAAgD8AAIA/TbtiPRSIoLppphE6L0YANVAWjToKiie5AACAPwAAgD9mD1Y9XKMpumaSrLvEnC62ckfNOtwSyDoAAIA/AACAPwAQHby/G7k/rc1vvZlVY730jQC9OFbuvAAAAAAAAAAAAHTwu4/eT7qwTG87aymltaXj4brubYq6AACAPwAAgD8Gtiy+HFg2vJ5vMLx663G6V1WiPTiCSTsAAIA/AACAPyZYhT1IG426TSOVOV5CdLUfCKw6GhyruAAAgD8AAIA/GrLAPYVjq7mYy1m8EEGeOoxxRTs6VYo7AAAAAAAAgD9Ay+c9XHMpur7Eeznv+lu2+0KZuoKRjrgAAAAAAACAP6b5or24Xre5KkVoui1nGrVSm6e7BsWJOQAAgD8AAIA/M7RLPSmgMbrjUnI7hPrTNU52srlSrI26AACAPwAAgD9mUC8+aOGOvD95xjzh21i7zgD5vaRaLLwAAIA/AACAP1p+tj328HW6rlw7O25fKbYPxDG7CVQetQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "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, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.6.0", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2db67c63664feefbf4c337c78d18cc635cb711093c76af5a0235261b8ab4a3c0
3
+ size 147140
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.0
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7ff0c2161440>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff0c21614d0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff0c2161560>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff0c21615f0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7ff0c2161680>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7ff0c2161710>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff0c21617a0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7ff0c2161830>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff0c21618c0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff0c2161950>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff0c21619e0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7ff0c21b3300>"
20
+ },
21
+ "verbose": 1,
22
+ "policy_kwargs": {},
23
+ "observation_space": {
24
+ ":type:": "<class 'gym.spaces.box.Box'>",
25
+ ":serialized:": "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",
26
+ "dtype": "float32",
27
+ "_shape": [
28
+ 8
29
+ ],
30
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
31
+ "high": "[inf inf inf inf inf inf inf inf]",
32
+ "bounded_below": "[False False False False False False False False]",
33
+ "bounded_above": "[False False False False False False False False]",
34
+ "_np_random": null
35
+ },
36
+ "action_space": {
37
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
38
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 16,
45
+ "num_timesteps": 507904,
46
+ "_total_timesteps": 500000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1661359363.7094195,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "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"
56
+ },
57
+ "_last_obs": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "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"
60
+ },
61
+ "_last_episode_starts": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
64
+ },
65
+ "_last_original_obs": null,
66
+ "_episode_num": 0,
67
+ "use_sde": false,
68
+ "sde_sample_freq": -1,
69
+ "_current_progress_remaining": -0.015808000000000044,
70
+ "ep_info_buffer": {
71
+ ":type:": "<class 'collections.deque'>",
72
+ ":serialized:": "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"
73
+ },
74
+ "ep_success_buffer": {
75
+ ":type:": "<class 'collections.deque'>",
76
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 124,
79
+ "n_steps": 1024,
80
+ "gamma": 0.999,
81
+ "gae_lambda": 0.98,
82
+ "ent_coef": 0.01,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 4,
87
+ "clip_range": {
88
+ ":type:": "<class 'function'>",
89
+ ":serialized:": "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"
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d3719989d8a50205255e21e27028b1cc073337ff14bf3497ffe6da3e5b6a6bea
3
+ size 87865
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c008c81276cb4b0a6437f31e3ae5a0ebca073b8f382cc78f474faefd3b8c1981
3
+ size 43201
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
2
+ Python: 3.7.13
3
+ Stable-Baselines3: 1.6.0
4
+ PyTorch: 1.12.1+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
Binary file (245 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 228.1685762683607, "std_reward": 17.09908403407852, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-08-24T16:58:09.970155"}