Upload PPO LunarLander-v2 trained agent
Browse files- README.md +36 -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 +1,36 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 |
+
- metrics:
|
12 |
+
- type: mean_reward
|
13 |
+
value: 211.67 +/- 17.03
|
14 |
+
name: mean_reward
|
15 |
+
task:
|
16 |
+
type: reinforcement-learning
|
17 |
+
name: reinforcement-learning
|
18 |
+
dataset:
|
19 |
+
name: LunarLander-v2
|
20 |
+
type: LunarLander-v2
|
21 |
+
---
|
22 |
+
|
23 |
+
# **PPO** Agent playing **LunarLander-v2**
|
24 |
+
This is a trained model of a **PPO** agent playing **LunarLander-v2**
|
25 |
+
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
|
26 |
+
|
27 |
+
## Usage (with Stable-baselines3)
|
28 |
+
TODO: Add your code
|
29 |
+
|
30 |
+
|
31 |
+
```python
|
32 |
+
from stable_baselines3 import ...
|
33 |
+
from huggingface_sb3 import load_from_hub
|
34 |
+
|
35 |
+
...
|
36 |
+
```
|
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 0x7f615ff06e60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f615ff06ef0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f615ff06f80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f615ff0e050>", "_build": "<function ActorCriticPolicy._build at 0x7f615ff0e0e0>", "forward": "<function ActorCriticPolicy.forward at 0x7f615ff0e170>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f615ff0e200>", "_predict": "<function ActorCriticPolicy._predict at 0x7f615ff0e290>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f615ff0e320>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f615ff0e3b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f615ff0e440>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f615ff558a0>"}, "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": 1664950292813262597, "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": "1.6.1", "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:d0d08c68dd81814f038a0639465c4c5e65d22cdb2b4e38da27facfdb2c5502ed
|
3 |
+
size 147150
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.1
|
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 0x7f615ff06e60>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f615ff06ef0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f615ff06f80>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f615ff0e050>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f615ff0e0e0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f615ff0e170>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f615ff0e200>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f615ff0e290>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f615ff0e320>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f615ff0e3b0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f615ff0e440>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f615ff558a0>"
|
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": 1664950292813262597,
|
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:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAHqpJj4Jtq4+1iMcvtUjU74PK3C7kg6WvQAAAAAAAAAATda+PcMpLbo2gg676UuVtd1pwTp6BCU6AACAPwAAgD+mOss97E64PsheGr4Jw1q+uW8tvVGJIL0AAAAAAAAAAGa2uDr23He6ip6IOQnz17VAiVy6VQaauAAAgD8AAIA/U282PhzUTbzFmHy6X6M4PBoXy72FmgE9AAAAAAAAAABAGSy+9OPAPtK8ZLyDk5m+0seJPbOhTrsAAAAAAAAAALMsO73heqa4aE+HOn4mCLXudAq8cx2iuQAAgD8AAIA/TaAtvj1jRDyXDB88R512uo+O1b07e207AACAPwAAgD+zJVK99oQ/unHVgLkPo220thnwOMYmlTgAAIA/AACAPzoQBj74qPc+Ke0FvS+Na77E+w+8amc1vQAAAAAAAAAAZgrpO8OxXLr5ghG6Uv4HtnObkjo3hSY5AACAPwAAgD/1y4++GiunPxhp2b6/yIe+wt6+vt+LhL0AAAAAAAAAAI2ylD1/ZtQ+K/rFPR0thr7Fiwy+lG4evQAAAAAAAAAATTPZPWddeD7SLJ+9/YKivgYGgD7udVI8AAAAAAAAAAAApOe9hUPyuW4DTbsn5544xn4yuvrl2jkAAIA/AACAP/1sdb64S6O7yydUOwLQRDhCUOc8f4UuuQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
|
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:e8950bac9cb8b39f7a240ef38b2117286f0755647ca7c794aa9ba945281c85a1
|
3 |
+
size 87865
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4c2e1f47f24374c507466273cbd37c94aaaf2acc07b3a22208471000e30ebe01
|
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: 1.6.1
|
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 (255 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 211.6699192590097, "std_reward": 17.027210330514517, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-05T06:26:39.030178"}
|