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 +95 -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 +7 -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: 252.13 +/- 22.06
|
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 0x7f8f9d82b280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8f9d82b310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8f9d82b3a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8f9d82b430>", "_build": "<function ActorCriticPolicy._build at 0x7f8f9d82b4c0>", "forward": "<function ActorCriticPolicy.forward at 0x7f8f9d82b550>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8f9d82b5e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8f9d82b670>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8f9d82b700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8f9d82b790>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8f9d82b820>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8f9d82b8b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f8f9d829510>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1676596219600061190, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f8d2f52ea31f04d36011fa1b190302f363eea27d5bc75c76942adcc99e87b9e0
|
3 |
+
size 147416
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,95 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7f8f9d82b280>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8f9d82b310>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8f9d82b3a0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8f9d82b430>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f8f9d82b4c0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f8f9d82b550>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8f9d82b5e0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8f9d82b670>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f8f9d82b700>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8f9d82b790>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8f9d82b820>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8f9d82b8b0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7f8f9d829510>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"observation_space": {
|
25 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
26 |
+
":serialized:": "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",
|
27 |
+
"dtype": "float32",
|
28 |
+
"_shape": [
|
29 |
+
8
|
30 |
+
],
|
31 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
32 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
33 |
+
"bounded_below": "[False False False False False False False False]",
|
34 |
+
"bounded_above": "[False False False False False False False False]",
|
35 |
+
"_np_random": null
|
36 |
+
},
|
37 |
+
"action_space": {
|
38 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
39 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
40 |
+
"n": 4,
|
41 |
+
"_shape": [],
|
42 |
+
"dtype": "int64",
|
43 |
+
"_np_random": null
|
44 |
+
},
|
45 |
+
"n_envs": 16,
|
46 |
+
"num_timesteps": 1015808,
|
47 |
+
"_total_timesteps": 1000000,
|
48 |
+
"_num_timesteps_at_start": 0,
|
49 |
+
"seed": null,
|
50 |
+
"action_noise": null,
|
51 |
+
"start_time": 1676596219600061190,
|
52 |
+
"learning_rate": 0.0003,
|
53 |
+
"tensorboard_log": null,
|
54 |
+
"lr_schedule": {
|
55 |
+
":type:": "<class 'function'>",
|
56 |
+
":serialized:": "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"
|
57 |
+
},
|
58 |
+
"_last_obs": {
|
59 |
+
":type:": "<class 'numpy.ndarray'>",
|
60 |
+
":serialized:": "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"
|
61 |
+
},
|
62 |
+
"_last_episode_starts": {
|
63 |
+
":type:": "<class 'numpy.ndarray'>",
|
64 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
65 |
+
},
|
66 |
+
"_last_original_obs": null,
|
67 |
+
"_episode_num": 0,
|
68 |
+
"use_sde": false,
|
69 |
+
"sde_sample_freq": -1,
|
70 |
+
"_current_progress_remaining": -0.015808000000000044,
|
71 |
+
"ep_info_buffer": {
|
72 |
+
":type:": "<class 'collections.deque'>",
|
73 |
+
":serialized:": "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"
|
74 |
+
},
|
75 |
+
"ep_success_buffer": {
|
76 |
+
":type:": "<class 'collections.deque'>",
|
77 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
78 |
+
},
|
79 |
+
"_n_updates": 248,
|
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 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:aeb411093bde838541cb3666febf4b272a8dd797fd6b763661036b1616a80d50
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f0458d0269bbde6735991a9d11eb17190a8b10592b542d72cf4e9bf9e97fcb49
|
3 |
+
size 43393
|
ppo-LunarLander-v2/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
ppo-LunarLander-v2/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
- Python: 3.8.10
|
3 |
+
- Stable-Baselines3: 1.7.0
|
4 |
+
- PyTorch: 1.13.1+cu116
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.21.6
|
7 |
+
- Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (227 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 252.13107613552538, "std_reward": 22.055173531335033, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-17T01:40:33.476320"}
|