Upload PPO LunarLander-v2 trained agent
Browse files- README.md +36 -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 +1,36 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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: 180.88 +/- 15.22
|
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 0x7f18213563b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1821356440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f18213564d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1821356560>", "_build": "<function ActorCriticPolicy._build at 0x7f18213565f0>", "forward": "<function ActorCriticPolicy.forward at 0x7f1821356680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1821356710>", "_predict": "<function ActorCriticPolicy._predict at 0x7f18213567a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1821356830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f18213568c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1821356950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f1821411e40>"}, "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": 1660062423.799343, "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-5.4.188+-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": "1.12.0+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:b247039cca388018c9e202ae600cc06d0755cee5da45cadd4a882696bd0e6e0a
|
3 |
+
size 147147
|
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 0x7f18213563b0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1821356440>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f18213564d0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1821356560>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f18213565f0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f1821356680>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1821356710>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f18213567a0>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1821356830>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f18213568c0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1821356950>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f1821411e40>"
|
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": 1660062423.799343,
|
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:a4676bb1878220fb83e168f701d8d7e035e263f340754de738bf7c6bb46a5af6
|
3 |
+
size 87865
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8ff61112a417ea362686c5d8aaf113ce77c18c093ef33b4b008aac45481b364b
|
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: 1.12.0+cu113
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (252 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 180.87708759506486, "std_reward": 15.216224018648326, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-08-09T17:13:37.558170"}
|