Upload trainder agent
Browse files- .gitattributes +1 -0
- README.md +36 -0
- config.json +1 -0
- ppo_lunarlander.zip +3 -0
- ppo_lunarlander/_stable_baselines3_version +1 -0
- ppo_lunarlander/data +94 -0
- ppo_lunarlander/policy.optimizer.pth +3 -0
- ppo_lunarlander/policy.pth +3 -0
- ppo_lunarlander/pytorch_variables.pth +3 -0
- ppo_lunarlander/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: 122.75 +/- 118.20
|
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 0x7f93a336c440>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f93a336c4d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f93a336c560>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f93a336c5f0>", "_build": "<function ActorCriticPolicy._build at 0x7f93a336c680>", "forward": "<function ActorCriticPolicy.forward at 0x7f93a336c710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f93a336c7a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f93a336c830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f93a336c8c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f93a336c950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f93a336c9e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f93a333f240>"}, "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": 1655659846.4136107, "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.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a15f796f9d6e7e20ab3c866b9b216725a24d2e8af4b6233cdecb497deffa91b1
|
3 |
+
size 144144
|
ppo_lunarlander/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.5.0
|
ppo_lunarlander/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 0x7f93a336c440>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f93a336c4d0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f93a336c560>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f93a336c5f0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f93a336c680>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f93a336c710>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f93a336c7a0>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f93a336c830>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f93a336c8c0>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f93a336c950>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f93a336c9e0>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f93a333f240>"
|
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": 1655659846.4136107,
|
51 |
+
"learning_rate": 0.0003,
|
52 |
+
"tensorboard_log": null,
|
53 |
+
"lr_schedule": {
|
54 |
+
":type:": "<class 'function'>",
|
55 |
+
":serialized:": "gASVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
|
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/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:91327aa21dac038408040e78ab20565c8a06867f22629d40f3bdf05361af445d
|
3 |
+
size 84829
|
ppo_lunarlander/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2750802b4799ad7caeb2570968c0c3d4a21019aef47320bcd55e37f57508a851
|
3 |
+
size 43201
|
ppo_lunarlander/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/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 sha256:34f994aba55446a4594bdd1661bde7dc5972a1ff8d60088988f13a1aa369e37f
|
3 |
+
size 244411
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 122.75299000325978, "std_reward": 118.19754402577253, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-19T17:52:50.225002"}
|