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: 252.68 +/- 16.73
|
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 0x7f36b5fd9040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f36b5fd90d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f36b5fd9160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f36b5fd91f0>", "_build": "<function ActorCriticPolicy._build at 0x7f36b5fd9280>", "forward": "<function ActorCriticPolicy.forward at 0x7f36b5fd9310>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f36b5fd93a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f36b5fd9430>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f36b5fd94c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f36b5fd9550>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f36b5fd95e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f36b5fd4480>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1673153346864843391, "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-glibc2.27 #1 SMP Sat Dec 10 16:00:40 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 sha256:6ee4e52d0e2a3491d95f0fef81f5faabb5cba58cbf49328bcd30a8abdecc7e15
|
3 |
+
size 147214
|
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 0x7f36b5fd9040>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f36b5fd90d0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f36b5fd9160>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f36b5fd91f0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f36b5fd9280>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f36b5fd9310>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f36b5fd93a0>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f36b5fd9430>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f36b5fd94c0>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f36b5fd9550>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f36b5fd95e0>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f36b5fd4480>"
|
20 |
+
},
|
21 |
+
"verbose": 1,
|
22 |
+
"policy_kwargs": {},
|
23 |
+
"observation_space": {
|
24 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
25 |
+
":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
|
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": 1673153346864843391,
|
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": 248,
|
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:eaa657312a418c7c676355a0c811ee8f57f711a284a380fd5d3d16391dd31eb7
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:83301578b5daf92ccdfe5d3eaa9bc7655ac46642f634860871c1561a408e262b
|
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-5.10.147+-x86_64-with-glibc2.27 #1 SMP Sat Dec 10 16:00:40 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 (227 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 252.6760657652343, "std_reward": 16.73497642951681, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-08T05:21:10.502960"}
|