first commit - model PPO performing good
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: 239.92 +/- 20.79
|
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 0x7fa50446e0d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa50446e160>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa50446e1f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa50446e280>", "_build": "<function ActorCriticPolicy._build at 0x7fa50446e310>", "forward": "<function ActorCriticPolicy.forward at 0x7fa50446e3a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa50446e430>", "_predict": "<function ActorCriticPolicy._predict at 0x7fa50446e4c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa50446e550>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa50446e5e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa50446e670>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fa504466a20>"}, "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": 1672993595955599206, "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-glibc2.27 #1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+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:c2cbba3f347189980acdbf002ae9a992ed7e3a178e37f3b64e27a31661cc9dbe
|
3 |
+
size 147218
|
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 0x7fa50446e0d0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa50446e160>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa50446e1f0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa50446e280>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fa50446e310>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fa50446e3a0>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa50446e430>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fa50446e4c0>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa50446e550>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa50446e5e0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa50446e670>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7fa504466a20>"
|
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": 1015808,
|
46 |
+
"_total_timesteps": 1000000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1672993595955599206,
|
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": 248,
|
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:efdc93126dbd6885a95e212bc498c08c845e25dc84c85ff1f0e3870a31733865
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6a5ee59516e1ab4d87b0bc46263ac6d5623c9e7dca996ba707f475699cedc420
|
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-5.10.147+-x86_64-with-glibc2.27 #1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
Python: 3.8.16
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.13.0+cu116
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (219 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 239.92169866976738, "std_reward": 20.791617039010347, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-06T08:49:26.545362"}
|