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 +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: 254.57 +/- 23.61
|
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 0x7997cc9c2b00>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7997cc9c2b90>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7997cc9c2c20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7997cc9c2cb0>", "_build": "<function ActorCriticPolicy._build at 0x7997cc9c2d40>", "forward": "<function ActorCriticPolicy.forward at 0x7997cc9c2dd0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7997cc9c2e60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7997cc9c2ef0>", "_predict": "<function ActorCriticPolicy._predict at 0x7997cc9c2f80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7997cc9c3010>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7997cc9c30a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7997cc9c3130>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7997ccb6d2c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718732258251776552, "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:": "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+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:fec099cfceb41480d21b96ca6d3d643296cd4b24ab7c2291714331a45fddb2b1
|
3 |
+
size 148080
|
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 0x7997cc9c2b00>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7997cc9c2b90>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7997cc9c2c20>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7997cc9c2cb0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7997cc9c2d40>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7997cc9c2dd0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7997cc9c2e60>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7997cc9c2ef0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7997cc9c2f80>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7997cc9c3010>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7997cc9c30a0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7997cc9c3130>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7997ccb6d2c0>"
|
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": 1718732258251776552,
|
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:": "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 sha256:724444a678faa569fcf75bbfdb82f1f6c3fe06d6522deb17f75ee60cfdd78521
|
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:d9d95db9bbae371d7c7fd7ceba4e8a6a5f181b1a65eb1ccbdf81f62f2256fce1
|
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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.3.0+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 (195 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 254.57008659999997, "std_reward": 23.609963019357867, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-18T18:10:11.769572"}
|