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: 253.28 +/- 15.40
|
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 0x7f0b88060dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0b88060e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0b88060ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0b88060f70>", "_build": "<function ActorCriticPolicy._build at 0x7f0b87fe4040>", "forward": "<function ActorCriticPolicy.forward at 0x7f0b87fe40d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f0b87fe4160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0b87fe41f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0b87fe4280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0b87fe4310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0b87fe43a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0b87fe4430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0b8805e450>"}, "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": 1676067442538538530, "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 sha256:88d28a18322cb05a70f3991b38d719f7a4e293e4cceca431f80798d640c02c21
|
3 |
+
size 147424
|
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 0x7f0b88060dc0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0b88060e50>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0b88060ee0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0b88060f70>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f0b87fe4040>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f0b87fe40d0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f0b87fe4160>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0b87fe41f0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f0b87fe4280>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0b87fe4310>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0b87fe43a0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0b87fe4430>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7f0b8805e450>"
|
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": 1676067442538538530,
|
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:d25918fa15ad9206202dba57be369a9f51da0f889b423f3b5013f227e3826919
|
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:ab63f4acca25bf547ac134cff96fdf162a1e7878244529b6458595a03b25643c
|
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 (219 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 253.27826419092767, "std_reward": 15.397079719667142, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-10T22:45:08.660339"}
|