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: 286.13 +/- 18.53
|
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 0x7cf5951d8ca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cf5951d8d30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cf5951d8dc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cf5951d8e50>", "_build": "<function ActorCriticPolicy._build at 0x7cf5951d8ee0>", "forward": "<function ActorCriticPolicy.forward at 0x7cf5951d8f70>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7cf5951d9000>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cf5951d9090>", "_predict": "<function ActorCriticPolicy._predict at 0x7cf5951d9120>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cf5951d91b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cf5951d9240>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7cf5951d92d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7cf59517c7c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1717246572892810584, "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": 620, "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": 10, "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:d3adcf3231b53a2a39dabfee6153b2ed6c82fd555bd17f441beaa4084bc79f90
|
3 |
+
size 147961
|
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 0x7cf5951d8ca0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cf5951d8d30>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cf5951d8dc0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cf5951d8e50>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7cf5951d8ee0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7cf5951d8f70>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7cf5951d9000>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cf5951d9090>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7cf5951d9120>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cf5951d91b0>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cf5951d9240>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7cf5951d92d0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7cf59517c7c0>"
|
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": 1717246572892810584,
|
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": 620,
|
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": 10,
|
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:f6b917e486ce91fa104dd66b690587a7692937bbee3e0f45e0b3cc4b6a5b8cbf
|
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:fad9961065c2039e1bd7a76543ae773bd5b1a6861a0a18c754657eb2fc0e3619
|
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 (167 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 286.13465669999994, "std_reward": 18.530335901848822, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-01T13:32:26.704803"}
|