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 +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: 251.83 +/- 22.51
|
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 0x7fac6589f310>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fac6589f3a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fac6589f430>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fac6589f4c0>", "_build": "<function ActorCriticPolicy._build at 0x7fac6589f550>", "forward": "<function ActorCriticPolicy.forward at 0x7fac6589f5e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fac6589f670>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fac6589f700>", "_predict": "<function ActorCriticPolicy._predict at 0x7fac6589f790>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fac6589f820>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fac6589f8b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fac6589f940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fac6589e2a0>"}, "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": 1675623277468177441, "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": "1.21.6", "Gym": "0.21.0"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6753394479a569b369ca2c9082fa98184c9aba1bcf2e4d57e20ccdbbdd5a2adb
|
3 |
+
size 147420
|
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 0x7fac6589f310>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fac6589f3a0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fac6589f430>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fac6589f4c0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fac6589f550>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fac6589f5e0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fac6589f670>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fac6589f700>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fac6589f790>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fac6589f820>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fac6589f8b0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fac6589f940>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7fac6589e2a0>"
|
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": 1675623277468177441,
|
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 sha256:8d53edca5b4a80f3d29a7d4614f42d9726627d50c1dff7381b2d29f1b901406e
|
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:ded9d87b919af574ffc5174caa8ce77701def0348727aa2da74aa5a3793d8d2a
|
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: 1.21.6
|
7 |
+
- Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (246 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 251.83473941870398, "std_reward": 22.50760233479437, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-05T19:18:55.035417"}
|