Added LunarLander-v2 model trained with PPO
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 +94 -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: 264.77 +/- 15.26
|
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 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 0x7f0756bca5e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0756bca670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0756bca700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0756bca790>", "_build": "<function ActorCriticPolicy._build at 0x7f0756bca820>", "forward": "<function ActorCriticPolicy.forward at 0x7f0756bca8b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0756bca940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0756bca9d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0756bcaa60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0756bcaaf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0756bcab80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0756c38de0>"}, "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": 1670620376007277410, "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": 496, "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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "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 sha256:9760b1928628f782692aaae6f74ea6c91007bfd5596fec81d097cb55a72dac59
|
3 |
+
size 147138
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.2
|
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 0x7f0756bca5e0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0756bca670>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0756bca700>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0756bca790>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f0756bca820>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f0756bca8b0>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0756bca940>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f0756bca9d0>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0756bcaa60>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0756bcaaf0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0756bcab80>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f0756c38de0>"
|
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": 1015808,
|
46 |
+
"_total_timesteps": 1000000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1670620376007277410,
|
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": 496,
|
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 sha256:6aab930e1508d4b20bd7f63c452c3976b5fc49ac82762a90638c8d27b5e12128
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:10db12080c7817a93561b2fe46a43ca523afbe5e84de9563386b9b0c291596fe
|
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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
|
2 |
+
Python: 3.8.16
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.13.0+cu116
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (198 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 264.7697146259705, "std_reward": 15.25637733675595, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-09T22:05:41.341380"}
|