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 +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: 265.47 +/- 17.56
|
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 0x7f4a3deef5e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4a3deef670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4a3deef700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4a3deef790>", "_build": "<function ActorCriticPolicy._build at 0x7f4a3deef820>", "forward": "<function ActorCriticPolicy.forward at 0x7f4a3deef8b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4a3deef940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f4a3deef9d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4a3deefa60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4a3deefaf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4a3deefb80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f4a3dee9e70>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1671495079426334183, "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": 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-5.10.133+-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:e404be7e45719b64503b9f6dec408c3b452c0f1e1cf69d7ff8a0dbfee6390e19
|
3 |
+
size 147204
|
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 0x7f4a3deef5e0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4a3deef670>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4a3deef700>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4a3deef790>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f4a3deef820>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f4a3deef8b0>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4a3deef940>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f4a3deef9d0>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4a3deefa60>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4a3deefaf0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4a3deefb80>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f4a3dee9e70>"
|
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": 1671495079426334183,
|
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 sha256:540a01f0937b7432f8c5a93843a1d2635f8f6e4141007722f2cd7eadb17eb0c1
|
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:f180210d8e03ed38beffaddd234d36d662e3833b1710ba1d72b2a9adbc195266
|
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 (229 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 265.46554466903666, "std_reward": 17.560644243021557, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-20T00:32:12.498490"}
|