The first RL model on Hugging Face!
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: 270.19 +/- 20.25
|
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 0x7f88ea4ca790>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f88ea4ca820>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f88ea4ca8b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f88ea4ca940>", "_build": "<function ActorCriticPolicy._build at 0x7f88ea4ca9d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f88ea4caa60>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f88ea4caaf0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f88ea4cab80>", "_predict": "<function ActorCriticPolicy._predict at 0x7f88ea4cac10>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f88ea4caca0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f88ea4cad30>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f88ea4cadc0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f88ea4c4b10>"}, "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": 1677170416334963238, "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 sha256:3975fa8243dedf3a5cb501f9cda931f4285e618175cf4bee3a5b58e7c5e00b7b
|
3 |
+
size 147408
|
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 0x7f88ea4ca790>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f88ea4ca820>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f88ea4ca8b0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f88ea4ca940>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f88ea4ca9d0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f88ea4caa60>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f88ea4caaf0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f88ea4cab80>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f88ea4cac10>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f88ea4caca0>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f88ea4cad30>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f88ea4cadc0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7f88ea4c4b10>"
|
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": 1677170416334963238,
|
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:fc54830976d07e2c6a337d0adc77f19968a0019a7685179c1286e14245f42611
|
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:f50d927f57d692b7b4a4ffc29a4a7b2b5e3dfd3e353465edb8759abca689aa03
|
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 (215 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 270.18694740047414, "std_reward": 20.25228016211537, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-23T17:13:53.855278"}
|