Upload PPO LunarLander-v2 trained agent
Browse files- README.md +37 -0
- config.json +1 -0
- ppo-LunarLander-v2.zip +3 -0
- ppo-LunarLander-v2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2/data +95 -0
- ppo-LunarLander-v2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2/policy.pth +3 -0
- ppo-LunarLander-v2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2/system_info.txt +7 -0
- replay.mp4 +0 -0
- results.json +1 -0
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: 251.68 +/- 21.16
|
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 0x7fdf9c05ab80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fdf9c05ac10>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fdf9c05aca0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fdf9c05ad30>", "_build": "<function ActorCriticPolicy._build at 0x7fdf9c05adc0>", "forward": "<function ActorCriticPolicy.forward at 0x7fdf9c05ae50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fdf9c05aee0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fdf9c05af70>", "_predict": "<function ActorCriticPolicy._predict at 0x7fdf9c05e040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fdf9c05e0d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fdf9c05e160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fdf9c05e1f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fdf9c0557b0>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677795849430511773, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8de7d03400006694ddd5f703e27a487a80b5b401beec4de1eaf0a90f434119e4
|
3 |
+
size 147368
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,95 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7fdf9c05ab80>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fdf9c05ac10>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fdf9c05aca0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fdf9c05ad30>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fdf9c05adc0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fdf9c05ae50>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fdf9c05aee0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fdf9c05af70>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fdf9c05e040>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fdf9c05e0d0>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fdf9c05e160>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fdf9c05e1f0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7fdf9c0557b0>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"observation_space": {
|
25 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
26 |
+
":serialized:": "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",
|
27 |
+
"dtype": "float32",
|
28 |
+
"_shape": [
|
29 |
+
8
|
30 |
+
],
|
31 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
32 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
33 |
+
"bounded_below": "[False False False False False False False False]",
|
34 |
+
"bounded_above": "[False False False False False False False False]",
|
35 |
+
"_np_random": null
|
36 |
+
},
|
37 |
+
"action_space": {
|
38 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
39 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
40 |
+
"n": 4,
|
41 |
+
"_shape": [],
|
42 |
+
"dtype": "int64",
|
43 |
+
"_np_random": null
|
44 |
+
},
|
45 |
+
"n_envs": 16,
|
46 |
+
"num_timesteps": 1015808,
|
47 |
+
"_total_timesteps": 1000000,
|
48 |
+
"_num_timesteps_at_start": 0,
|
49 |
+
"seed": null,
|
50 |
+
"action_noise": null,
|
51 |
+
"start_time": 1677795849430511773,
|
52 |
+
"learning_rate": 0.0003,
|
53 |
+
"tensorboard_log": null,
|
54 |
+
"lr_schedule": {
|
55 |
+
":type:": "<class 'function'>",
|
56 |
+
":serialized:": "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"
|
57 |
+
},
|
58 |
+
"_last_obs": {
|
59 |
+
":type:": "<class 'numpy.ndarray'>",
|
60 |
+
":serialized:": "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"
|
61 |
+
},
|
62 |
+
"_last_episode_starts": {
|
63 |
+
":type:": "<class 'numpy.ndarray'>",
|
64 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
65 |
+
},
|
66 |
+
"_last_original_obs": null,
|
67 |
+
"_episode_num": 0,
|
68 |
+
"use_sde": false,
|
69 |
+
"sde_sample_freq": -1,
|
70 |
+
"_current_progress_remaining": -0.015808000000000044,
|
71 |
+
"ep_info_buffer": {
|
72 |
+
":type:": "<class 'collections.deque'>",
|
73 |
+
":serialized:": "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"
|
74 |
+
},
|
75 |
+
"ep_success_buffer": {
|
76 |
+
":type:": "<class 'collections.deque'>",
|
77 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
78 |
+
},
|
79 |
+
"_n_updates": 248,
|
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 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9b4d7094d55ee8549c28abe6b58cd57f5b85f0c940813d2e24df601fb0b85717
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b96210fe505faf7b4975f29703215fb4188bb53011cc20f5dd70cbd1b1cbf970
|
3 |
+
size 43393
|
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-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
- Python: 3.8.10
|
3 |
+
- Stable-Baselines3: 1.7.0
|
4 |
+
- PyTorch: 1.13.1+cu116
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.22.4
|
7 |
+
- Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (234 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 251.67904420421405, "std_reward": 21.155668497497107, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-02T22:49:16.833683"}
|