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 +99 -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 +9 -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: 248.78 +/- 15.26
|
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 0x7a3ff4289a20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a3ff4289ab0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a3ff4289b40>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a3ff4289bd0>", "_build": "<function ActorCriticPolicy._build at 0x7a3ff4289c60>", "forward": "<function ActorCriticPolicy.forward at 0x7a3ff4289cf0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a3ff4289d80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a3ff4289e10>", "_predict": "<function ActorCriticPolicy._predict at 0x7a3ff4289ea0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a3ff4289f30>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a3ff4289fc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a3ff428a050>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a3ff428c9c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1696280008656934443, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d1d45119e4abc0541b69bf00a5da6708f61b7abe528124021b0767affc851724
|
3 |
+
size 146743
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,99 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7a3ff4289a20>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a3ff4289ab0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a3ff4289b40>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a3ff4289bd0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7a3ff4289c60>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7a3ff4289cf0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7a3ff4289d80>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a3ff4289e10>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7a3ff4289ea0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a3ff4289f30>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a3ff4289fc0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7a3ff428a050>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7a3ff428c9c0>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1015808,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1696280008656934443,
|
30 |
+
"learning_rate": 0.0003,
|
31 |
+
"tensorboard_log": null,
|
32 |
+
"_last_obs": {
|
33 |
+
":type:": "<class 'numpy.ndarray'>",
|
34 |
+
":serialized:": "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"
|
35 |
+
},
|
36 |
+
"_last_episode_starts": {
|
37 |
+
":type:": "<class 'numpy.ndarray'>",
|
38 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
39 |
+
},
|
40 |
+
"_last_original_obs": null,
|
41 |
+
"_episode_num": 0,
|
42 |
+
"use_sde": false,
|
43 |
+
"sde_sample_freq": -1,
|
44 |
+
"_current_progress_remaining": -0.015808000000000044,
|
45 |
+
"_stats_window_size": 100,
|
46 |
+
"ep_info_buffer": {
|
47 |
+
":type:": "<class 'collections.deque'>",
|
48 |
+
":serialized:": "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"
|
49 |
+
},
|
50 |
+
"ep_success_buffer": {
|
51 |
+
":type:": "<class 'collections.deque'>",
|
52 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
53 |
+
},
|
54 |
+
"_n_updates": 248,
|
55 |
+
"observation_space": {
|
56 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
+
":serialized:": "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",
|
58 |
+
"dtype": "float32",
|
59 |
+
"bounded_below": "[ True True True True True True True True]",
|
60 |
+
"bounded_above": "[ True True True True True True True True]",
|
61 |
+
"_shape": [
|
62 |
+
8
|
63 |
+
],
|
64 |
+
"low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
65 |
+
"high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
66 |
+
"low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
67 |
+
"high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
68 |
+
"_np_random": null
|
69 |
+
},
|
70 |
+
"action_space": {
|
71 |
+
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
72 |
+
":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": null
|
78 |
+
},
|
79 |
+
"n_envs": 16,
|
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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
|
91 |
+
},
|
92 |
+
"clip_range_vf": null,
|
93 |
+
"normalize_advantage": true,
|
94 |
+
"target_kl": null,
|
95 |
+
"lr_schedule": {
|
96 |
+
":type:": "<class 'function'>",
|
97 |
+
":serialized:": "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"
|
98 |
+
}
|
99 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6f0b50d0fb63791dce5cbc9d3935672081629966be5449807e1c1fd6a3b04cf0
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9a22967e7e847e19bb84360a69c73fc027d75fd80a94acfb4573bcb4e48fbec5
|
3 |
+
size 43329
|
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 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.0.1+cu118
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.23.5
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
Binary file (194 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 248.78076981552653, "std_reward": 15.257588895886435, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-02T21:16:24.365560"}
|