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: 164.58 +/- 87.78
|
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 0x7f883c35eb00>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f883c35eb90>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f883c35ec20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f883c35ecb0>", "_build": "<function ActorCriticPolicy._build at 0x7f883c35ed40>", "forward": "<function ActorCriticPolicy.forward at 0x7f883c35edd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f883c35ee60>", "_predict": "<function ActorCriticPolicy._predict at 0x7f883c35eef0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f883c35ef80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f883c2e4050>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f883c2e40e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f883c3289c0>"}, "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": 1658648662.7210667, "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:d24509d5547123adbcc8ed39e64607b146b2ee08448e22bd613900b89b96e696
|
3 |
+
size 147140
|
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 0x7f883c35eb00>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f883c35eb90>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f883c35ec20>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f883c35ecb0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f883c35ed40>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f883c35edd0>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f883c35ee60>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f883c35eef0>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f883c35ef80>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f883c2e4050>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f883c2e40e0>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f883c3289c0>"
|
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": 1658648662.7210667,
|
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 sha256:0c77baf650d1ae1fa011d52b09c8d9ca4c85439416c22339c1b4fb4765c16f01
|
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:dff9c7271cf0ff1f4acda0531be64de028fee03de797c85c82b8bc36c3711ee3
|
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 (241 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 164.57916732892068, "std_reward": 87.78331703430844, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-07-24T08:09:11.980080"}
|