Upload PPO LunarLander-v2 trained agent
Browse files- README.md +35 -1
- 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
CHANGED
@@ -1,3 +1,37 @@
|
|
1 |
---
|
2 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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: 252.23 +/- 19.70
|
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 0x78c8aee0e3b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78c8aee0e440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78c8aee0e4d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78c8aee0e560>", "_build": "<function ActorCriticPolicy._build at 0x78c8aee0e5f0>", "forward": "<function ActorCriticPolicy.forward at 0x78c8aee0e680>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78c8aee0e710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78c8aee0e7a0>", "_predict": "<function ActorCriticPolicy._predict at 0x78c8aee0e830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78c8aee0e8c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78c8aee0e950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78c8aee0e9e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78c8aee14340>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1705456593471441072, "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": -0.015808000000000044, "_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": 248, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "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:ee29d3881cce44a4218d4aa4012d1535dcc7da9a7211436c977cb1855514a32c
|
3 |
+
size 148052
|
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 0x78c8aee0e3b0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78c8aee0e440>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78c8aee0e4d0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78c8aee0e560>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x78c8aee0e5f0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x78c8aee0e680>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x78c8aee0e710>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78c8aee0e7a0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x78c8aee0e830>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78c8aee0e8c0>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78c8aee0e950>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x78c8aee0e9e0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x78c8aee14340>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1015808,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1705456593471441072,
|
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": -0.015808000000000044,
|
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": 248,
|
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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
|
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 sha256:580a6e414927d2f99bc7c532dbad804cfefc6fa07d6486a0a149af422ece9581
|
3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:37f163c72a862bf0456336c39a7d2a7d7b1edca9bf5330f80d5cb9d2b1499066
|
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: 2.1.0+cu121
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.23.5
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
Binary file (196 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 252.23186980208106, "std_reward": 19.701587447134493, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-01-17T02:39:07.134301"}
|