Upload PPO LunarLander-v2 trained agent
Browse files- .gitattributes +1 -0
- 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 +3 -0
- results.json +1 -0
.gitattributes
CHANGED
@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
25 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
26 |
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
27 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
25 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
26 |
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
27 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
28 |
+
*.mp4 filter=lfs diff=lfs merge=lfs -text
|
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: 182.30 +/- 78.62
|
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:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7fb238e80830>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb238e808c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb238e80950>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb238e809e0>", "_build": "<function ActorCriticPolicy._build at 0x7fb238e80a70>", "forward": "<function ActorCriticPolicy.forward at 0x7fb238e80b00>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb238e80b90>", "_predict": "<function ActorCriticPolicy._predict at 0x7fb238e80c20>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb238e80cb0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb238e80d40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb238e80dd0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fb238e5c090>"}, "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1656388528.6793358, "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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="}, "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+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:b76b0615179a8674149a1d7c03ea55d902230733d36e2049d02c0bc7f60215db
|
3 |
+
size 144136
|
ppo_LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.5.0
|
ppo_LunarLander-v2/data
ADDED
@@ -0,0 +1,94 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"policy_class": {
|
3 |
+
":type:": "<class 'abc.ABCMeta'>",
|
4 |
+
":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
|
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 0x7fb238e80830>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb238e808c0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb238e80950>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb238e809e0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fb238e80a70>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fb238e80b00>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb238e80b90>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fb238e80c20>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb238e80cb0>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb238e80d40>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb238e80dd0>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7fb238e5c090>"
|
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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1656388528.6793358,
|
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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="
|
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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
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:f51c267706f5f8cfe0d1d7f05385a7946a2edd3106c48694deca1b7ee865a209
|
3 |
+
size 84829
|
ppo_LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e765704178ac74787db79100af3e4ff4c5a47510adb4d2f96534d994fb4e3184
|
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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
|
2 |
+
Python: 3.7.13
|
3 |
+
Stable-Baselines3: 1.5.0
|
4 |
+
PyTorch: 1.11.0+cu113
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:985bf91ac12525e450a7873e696c772a533ad5186b5dccf3fe638430907450a1
|
3 |
+
size 238526
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 182.29751753468696, "std_reward": 78.61612442941218, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-28T04:19:44.089333"}
|