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 +94 -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: 229.93 +/- 43.18
|
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7fcf0bc2edd0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcf0bc2ee60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcf0bc2eef0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcf0bc2ef80>", "_build": "<function ActorCriticPolicy._build at 0x7fcf0bc37050>", "forward": "<function ActorCriticPolicy.forward at 0x7fcf0bc370e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcf0bc37170>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcf0bc37200>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcf0bc37290>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcf0bc37320>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcf0bc373b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcf0bc882d0>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1665821854047578033, "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": 124, "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-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.14", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "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 sha256:7359cd810fd16d3023c2c3eb058dd6f31017882bb5e529ed6e7a2c8077d5be6c
|
3 |
+
size 147134
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.2
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,94 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7fcf0bc2edd0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcf0bc2ee60>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcf0bc2eef0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcf0bc2ef80>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fcf0bc37050>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fcf0bc370e0>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcf0bc37170>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fcf0bc37200>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcf0bc37290>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcf0bc37320>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcf0bc373b0>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7fcf0bc882d0>"
|
20 |
+
},
|
21 |
+
"verbose": 1,
|
22 |
+
"policy_kwargs": {},
|
23 |
+
"observation_space": {
|
24 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
25 |
+
":serialized:": "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",
|
26 |
+
"dtype": "float32",
|
27 |
+
"_shape": [
|
28 |
+
8
|
29 |
+
],
|
30 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
31 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
32 |
+
"bounded_below": "[False False False False False False False False]",
|
33 |
+
"bounded_above": "[False False False False False False False False]",
|
34 |
+
"_np_random": null
|
35 |
+
},
|
36 |
+
"action_space": {
|
37 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
38 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
39 |
+
"n": 4,
|
40 |
+
"_shape": [],
|
41 |
+
"dtype": "int64",
|
42 |
+
"_np_random": null
|
43 |
+
},
|
44 |
+
"n_envs": 16,
|
45 |
+
"num_timesteps": 507904,
|
46 |
+
"_total_timesteps": 500000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1665821854047578033,
|
51 |
+
"learning_rate": 0.0003,
|
52 |
+
"tensorboard_log": null,
|
53 |
+
"lr_schedule": {
|
54 |
+
":type:": "<class 'function'>",
|
55 |
+
":serialized:": "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"
|
56 |
+
},
|
57 |
+
"_last_obs": {
|
58 |
+
":type:": "<class 'numpy.ndarray'>",
|
59 |
+
":serialized:": "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"
|
60 |
+
},
|
61 |
+
"_last_episode_starts": {
|
62 |
+
":type:": "<class 'numpy.ndarray'>",
|
63 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
64 |
+
},
|
65 |
+
"_last_original_obs": null,
|
66 |
+
"_episode_num": 0,
|
67 |
+
"use_sde": false,
|
68 |
+
"sde_sample_freq": -1,
|
69 |
+
"_current_progress_remaining": -0.015808000000000044,
|
70 |
+
"ep_info_buffer": {
|
71 |
+
":type:": "<class 'collections.deque'>",
|
72 |
+
":serialized:": "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"
|
73 |
+
},
|
74 |
+
"ep_success_buffer": {
|
75 |
+
":type:": "<class 'collections.deque'>",
|
76 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
77 |
+
},
|
78 |
+
"_n_updates": 124,
|
79 |
+
"n_steps": 1024,
|
80 |
+
"gamma": 0.999,
|
81 |
+
"gae_lambda": 0.98,
|
82 |
+
"ent_coef": 0.01,
|
83 |
+
"vf_coef": 0.5,
|
84 |
+
"max_grad_norm": 0.5,
|
85 |
+
"batch_size": 64,
|
86 |
+
"n_epochs": 4,
|
87 |
+
"clip_range": {
|
88 |
+
":type:": "<class 'function'>",
|
89 |
+
":serialized:": "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"
|
90 |
+
},
|
91 |
+
"clip_range_vf": null,
|
92 |
+
"normalize_advantage": true,
|
93 |
+
"target_kl": null
|
94 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2aa65100e1c6a284d46bea7cad0e8d3dba0265c3856dfa8022e4f47bdc7a7b6e
|
3 |
+
size 87865
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1c0c1e6790029be141c3dc285b5884a54dd43b48369c49a1c6845d3827fe3c58
|
3 |
+
size 43201
|
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-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022
|
2 |
+
Python: 3.7.14
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.12.1+cu113
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (186 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 229.9317637826594, "std_reward": 43.180759656758354, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-15T08:53:29.163246"}
|