Upload PPO LunarLander-v2 trained agent
Browse files- .gitattributes +1 -0
- 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 +3 -0
- results.json +1 -0
.gitattributes
CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
36 |
+
replay.mp4 filter=lfs diff=lfs merge=lfs -text
|
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: -525.44 +/- 120.14
|
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 0x79d709a193a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79d709a19440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79d709a194e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79d709a19580>", "_build": "<function ActorCriticPolicy._build at 0x79d709a19620>", "forward": "<function ActorCriticPolicy.forward at 0x79d709a196c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79d709a19760>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79d709a19800>", "_predict": "<function ActorCriticPolicy._predict at 0x79d709a198a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79d709a19940>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79d709a199e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79d709a19a80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79d709b0b900>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 8016, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1750621230423648761, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 1.0, "_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": 0, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "False", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "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:bfe58bc634a7f26dd724bfba2a07092c5b1216e0065cb4a8d9bd898884a8b105
|
3 |
+
size 59808
|
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 0x79d709a193a0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79d709a19440>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79d709a194e0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79d709a19580>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x79d709a19620>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x79d709a196c0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x79d709a19760>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79d709a19800>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x79d709a198a0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79d709a19940>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79d709a199e0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x79d709a19a80>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x79d709b0b900>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 8016,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1750621230423648761,
|
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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
|
39 |
+
},
|
40 |
+
"_last_original_obs": null,
|
41 |
+
"_episode_num": 0,
|
42 |
+
"use_sde": false,
|
43 |
+
"sde_sample_freq": -1,
|
44 |
+
"_current_progress_remaining": 1.0,
|
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": 0,
|
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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
|
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 sha256:13dbf41e305d3a0b52e13b973ece0bb28ffca5bcf57636bcf9b68102feec544e
|
3 |
+
size 1120
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8e1414487988e92c76d3e9f65a48fb6ec26c69c4634a4d6331f3ad2f77c72c15
|
3 |
+
size 43634
|
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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025
|
2 |
+
- Python: 3.11.13
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.6.0+cu124
|
5 |
+
- GPU Enabled: False
|
6 |
+
- Numpy: 2.0.2
|
7 |
+
- Cloudpickle: 3.1.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4930265fcebcc4acfcd58ac1e29281fb7aa2875861fc4e6a271b4af3f81d5f57
|
3 |
+
size 210822
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": -525.436169583723, "std_reward": 120.14438390315159, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-06-22T19:54:33.836453"}
|