Commit
•
8fbe8fd
1
Parent(s):
46011cf
first deeprl lunarlander model
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 +99 -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 +9 -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: -178.52 +/- 84.72
|
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 0x78175e631630>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78175e6316c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78175e631750>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78175e6317e0>", "_build": "<function ActorCriticPolicy._build at 0x78175e631870>", "forward": "<function ActorCriticPolicy.forward at 0x78175e631900>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78175e631990>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78175e631a20>", "_predict": "<function ActorCriticPolicy._predict at 0x78175e631ab0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78175e631b40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78175e631bd0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78175e631c60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78175e5c7f80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 16384, "_total_timesteps": 1000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713805252166709344, "learning_rate": 0.0003, "tensorboard_log": null, "_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": -15.384, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 4, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d5a2b8da8d6338391403c6e35213f81bdce363f9c2e0f34d9285526086592cbb
|
3 |
+
size 147931
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,99 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x78175e631630>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78175e6316c0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78175e631750>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78175e6317e0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x78175e631870>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x78175e631900>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x78175e631990>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78175e631a20>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x78175e631ab0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78175e631b40>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78175e631bd0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x78175e631c60>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x78175e5c7f80>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 16384,
|
25 |
+
"_total_timesteps": 1000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1713805252166709344,
|
30 |
+
"learning_rate": 0.0003,
|
31 |
+
"tensorboard_log": null,
|
32 |
+
"_last_obs": {
|
33 |
+
":type:": "<class 'numpy.ndarray'>",
|
34 |
+
":serialized:": "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"
|
35 |
+
},
|
36 |
+
"_last_episode_starts": {
|
37 |
+
":type:": "<class 'numpy.ndarray'>",
|
38 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
39 |
+
},
|
40 |
+
"_last_original_obs": null,
|
41 |
+
"_episode_num": 0,
|
42 |
+
"use_sde": false,
|
43 |
+
"sde_sample_freq": -1,
|
44 |
+
"_current_progress_remaining": -15.384,
|
45 |
+
"_stats_window_size": 100,
|
46 |
+
"ep_info_buffer": {
|
47 |
+
":type:": "<class 'collections.deque'>",
|
48 |
+
":serialized:": "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"
|
49 |
+
},
|
50 |
+
"ep_success_buffer": {
|
51 |
+
":type:": "<class 'collections.deque'>",
|
52 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
53 |
+
},
|
54 |
+
"_n_updates": 4,
|
55 |
+
"observation_space": {
|
56 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
+
":serialized:": "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",
|
58 |
+
"dtype": "float32",
|
59 |
+
"bounded_below": "[ True True True True True True True True]",
|
60 |
+
"bounded_above": "[ True True True True True True True True]",
|
61 |
+
"_shape": [
|
62 |
+
8
|
63 |
+
],
|
64 |
+
"low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
65 |
+
"high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
66 |
+
"low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
67 |
+
"high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
68 |
+
"_np_random": null
|
69 |
+
},
|
70 |
+
"action_space": {
|
71 |
+
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
72 |
+
":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": null
|
78 |
+
},
|
79 |
+
"n_envs": 16,
|
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 |
+
"lr_schedule": {
|
96 |
+
":type:": "<class 'function'>",
|
97 |
+
":serialized:": "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"
|
98 |
+
}
|
99 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f01a70f42a1e0f95258b5fd847210866a503d85e36a3be5f39f4ae52aaa5d95c
|
3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6bb83d2c0cc84268602b8e4f02e7b32b7e3c23c130871a30840465885a082eb2
|
3 |
+
size 43762
|
ppo-LunarLander-v2/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
|
3 |
+
size 864
|
ppo-LunarLander-v2/system_info.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.2.1+cu121
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.25.2
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
Binary file (154 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": -178.5244998, "std_reward": 84.71663332617986, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-22T17:13:51.266160"}
|