Upload PPO LunarLander-v2 trained agent
Browse files- .gitattributes +1 -0
- 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 +3 -0
- results.json +1 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
replay.mp4 filter=lfs diff=lfs merge=lfs -text
|
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: 263.61 +/- 14.61
|
| 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 0x7c0ffd3b3ec0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c0ffd3b3f60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c0ffd3b8040>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c0ffd3b80e0>", "_build": "<function ActorCriticPolicy._build at 0x7c0ffd3b8180>", "forward": "<function ActorCriticPolicy.forward at 0x7c0ffd3b8220>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c0ffd3b82c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c0ffd3b8360>", "_predict": "<function ActorCriticPolicy._predict at 0x7c0ffd3b8400>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c0ffd3b84a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c0ffd3b8540>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c0ffd3b85e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c0ffd73efc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1756898867142531785, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAAAAY7u97/w2P9F6lbt28I++dFfevbiWEj0AAAAAAAAAAJqf370SW7Q+GbkDPr2Rgb5DiYK7Hr3bPQAAAAAAAAAAzfZrvCkwILpjhx+85BY6OzluEbk+qhm8AACAPwAAgD+aZRS8XANyuj2GIrMK1TMvvWgqOtD60TMAAIA/AACAPwBTN732rC+6H0giOcA9wjPMkQe6I1w6uAAAgD8AAIA/5lwePTOFtT+wXgc/GaENvTiGlrvqcaw9AAAAAAAAAAAznTe8Kaw8O74OFr28O5q+CsoYvfXFWr0AAAAAAAAAAArle74j1os/onJcvvr0o77Bmrm+wWs7PQAAAAAAAAAAk6NuPkA7tT+W6xY/TBrTvnhhjj7IylM+AAAAAAAAAACa2JI9AQoUP20HXr6sqbW+nVlOvaRxuL0AAAAAAAAAANpx6b3Xul0/+2pyPapfq744p2m9Uhq5PQAAAAAAAAAAAKrMvIdB3D7yhv89vTmRvhH2Zz1QlA+9AAAAAAAAAACaGZk8Hx2zuS7eXrlAh++zmuOeupbwgDgAAIA/AACAPzovhj7LrWY/ml91PvCb+L5mLNA+0R1LPQAAAAAAAAAAAIApOePUtD+la7I7cxpAOjZpOrme5J+6AAAAAAAAAACAjko9A10RvJj/EDxp8ZA8BsxpvaJycT0AAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLEEsIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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:": "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"}, "system_info": {"OS": "Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.12.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.8.0+cu126", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "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 sha256:6a99e49288f8f47deed781fd0ff1b334884559d5c93b678d5f4ff31c12a8b4bb
|
| 3 |
+
size 149163
|
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 0x7c0ffd3b3ec0>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c0ffd3b3f60>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c0ffd3b8040>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c0ffd3b80e0>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7c0ffd3b8180>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7c0ffd3b8220>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7c0ffd3b82c0>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c0ffd3b8360>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7c0ffd3b8400>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c0ffd3b84a0>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c0ffd3b8540>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7c0ffd3b85e0>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7c0ffd73efc0>"
|
| 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": 1756898867142531785,
|
| 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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
|
| 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:": "gAWVKwwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQG9R+TFERaqMAWyUTUEBjAF0lEdAjb5jxkNF0HV9lChoBkdAco7/ZuhsZmgHTQwBaAhHQI2/6m8/Uvx1fZQoaAZHQG+R8ujASFpoB00TAWgIR0CNwLKxLTQWdX2UKGgGR0BzUQW3z+WGaAdNCgFoCEdAjcFef7Jnx3V9lChoBkdAcmiwUxmCiGgHTSwBaAhHQI3BrpcHGCJ1fZQoaAZHQG7TpHRTjvNoB00RAWgIR0CNwinxaxHHdX2UKGgGR0ByeWVD8cdYaAdL/GgIR0CNwiqc3EQ5dX2UKGgGR0BwPIbZOBUaaAdNIAFoCEdAjcMY6XBxgnV9lChoBkdAc5J/xlQMyGgHS/BoCEdAjcMvw3HaOHV9lChoBkdAbfs+9rXUY2gHTR4BaAhHQI3D+afBeol1fZQoaAZHQEb38VHnU2FoB0u/aAhHQI3FW7z06HV1fZQoaAZHQHB1lb/wRXhoB00eAWgIR0CNxiTdtVJddX2UKGgGR0BCvo2n889waAdLyWgIR0CNx/Whh6SldX2UKGgGR0Bxq3pV0cOtaAdNJgFoCEdAjchYDTz/ZXV9lChoBkdAcMy6FuejEmgHTRwBaAhHQI3J0WsRxtJ1fZQoaAZHQHL6CX2M85loB0vdaAhHQI3LMPnSv1V1fZQoaAZHQHEooDPnjhloB00JAWgIR0CNzEK8cuJ2dX2UKGgGR0Bvi4IY3vQXaAdL/GgIR0CNzbwMpgCwdX2UKGgGR0BxhbqLS/j9aAdNFQJoCEdAjc3ctf5ULnV9lChoBkdAcuTHtF8XvmgHTQEBaAhHQI3OmBas6q91fZQoaAZHQGzp0bDMvAZoB0v/aAhHQI3OwqLCN0h1fZQoaAZHQHEkN7a7EpBoB0v1aAhHQI3PpJRO1v51fZQoaAZHQHMxawD/2kBoB0voaAhHQI3RcAggX/J1fZQoaAZHQHHSsMmWt2doB00sAWgIR0CN0Yqgh8pkdX2UKGgGR0BvS6CDmKZVaAdNLgFoCEdAjdGlRP420nV9lChoBkdAcqReSjgydmgHTQgBaAhHQI3Rr2xptaZ1fZQoaAZHQHGS903fhuRoB00qAWgIR0CN0p/YJ3PidX2UKGgGR0BxaA24uscRaAdNFAFoCEdAjdRjn/1g6XV9lChoBkdAce8pXIU8FWgHTQMBaAhHQI3VeiDdxhl1fZQoaAZHQHI/puuRs/JoB00JAWgIR0CN1hY6nzg/dX2UKGgGR0Btwb3h4t6HaAdL/2gIR0CN2EPMjeKsdX2UKGgGR0BwbYO5J9RaaAdL/GgIR0CN2SThYNiIdX2UKGgGR0By7qmpEQXiaAdNOQFoCEdAjdoS+QEIPnV9lChoBkdAcf6CA+Y+jmgHTQIBaAhHQI3a1wDNhVl1fZQoaAZHQHD5L9MsYl9oB00CAWgIR0CN2vcPe54GdX2UKGgGR0Buohj+aScLaAdNBwFoCEdAjdwgpKBd2XV9lChoBkdARLI/7iyY5WgHS9ZoCEdAjdxkPUaybHV9lChoBkdAbk9D50r9VGgHTQABaAhHQI3cspmVZ9x1fZQoaAZHQG46c8kleGBoB00lAWgIR0CN3YTEit7sdX2UKGgGR0BwiwFcIJJHaAdNAQFoCEdAjd6aFmFrVXV9lChoBkdAbvJlBhQWN2gHTQgBaAhHQI3ewnhKlHl1fZQoaAZHQHHJgIUrTYxoB000AWgIR0COBzQ0oBq9dX2UKGgGR0BxQrwjMV1waAdNNAFoCEdAjggh42S+xnV9lChoBkdAbtYLS/j81mgHS/poCEdAjghO+AVfu3V9lChoBkdAclIWNFSbY2gHTSIBaAhHQI4JK0F8ohJ1fZQoaAZHQHEiucMEzO5oB0vjaAhHQI4KskfLcKx1fZQoaAZHQHEYQ+lj3EhoB00MAWgIR0CODAM2FWXDdX2UKGgGR0BtDEfs/pt8aAdNEQFoCEdAjg49v0h/zHV9lChoBkdActx0ZFXq7mgHS/BoCEdAjg6OvECNj3V9lChoBkdAbOGblRxcV2gHTRwBaAhHQI4PyMzdk8R1fZQoaAZHQHJo9KdxyXFoB00cAWgIR0COD+mnfl6rdX2UKGgGR0Bwein5zo2XaAdNAQFoCEdAjhA+f7Jnx3V9lChoBkdAcnVj0+TvA2gHTaIBaAhHQI4SE2gnMMZ1fZQoaAZHQHCHpVOsT39oB00rAWgIR0COEiH5aePJdX2UKGgGR0BxTUXDWK/EaAdNIwFoCEdAjhLTxoZhrnV9lChoBkdAc1ez0Yj0MGgHTQoBaAhHQI4S6/0ulGh1fZQoaAZHQG7x31anrIJoB00dAWgIR0COE6E+xGDudX2UKGgGR0BwBusIVuaXaAdNAgFoCEdAjhWhlMAWBXV9lChoBkdAbLr9qk/KQ2gHTRgBaAhHQI4V65mRNh51fZQoaAZHQHGDSGBWge1oB00ZAWgIR0COFuYUFjd6dX2UKGgGR0BxKRm9QGfPaAdNLAFoCEdAjhjQNCqp+HV9lChoBkdAc1nPRRdhRmgHTQcBaAhHQI4Z0Mb3oLZ1fZQoaAZHQFAG2aUiY9hoB0vPaAhHQI4anCTEBKd1fZQoaAZHQG3N5mqYJE9oB00xAWgIR0COGq/336AOdX2UKGgGR0BwzDJkoWpIaAdNBwFoCEdAjhwLUTcqOXV9lChoBkdAcSSGgzxgA2gHTSMBaAhHQI4dRB7eEZl1fZQoaAZHQHDI74WUKRdoB00LAWgIR0COHWveP7vYdX2UKGgGR0BxP3KEFnqWaAdNGgFoCEdAjh4GZE2HcnV9lChoBkdAciaOpKjBVWgHS/RoCEdAjh/XwCr923V9lChoBkdAc911g6U7jmgHS9hoCEdAjiCc9fTkQ3V9lChoBkdAcoM+FlCkXWgHTRYBaAhHQI4g4nhKlHl1fZQoaAZHQHLQx3A2ycFoB00vAWgIR0COIVC3PRiPdX2UKGgGR0BwvOf8MuvmaAdNLgFoCEdAjiFR5C4SYnV9lChoBkdAcpVbeMyaeGgHTSMBaAhHQI4hc/MW43F1fZQoaAZHQG4f+pn6EaloB00VAWgIR0COI5vVmSQpdX2UKGgGR0BzOqZfD1oQaAdNNgFoCEdAjiZSTpxFRnV9lChoBkdAcjQXL/0dzWgHTRIBaAhHQI4mZvitJWh1fZQoaAZHQG7HhWYF7ldoB00JAWgIR0COJ7pAUtZndX2UKGgGR0Bw9GNfgJkYaAdNHgFoCEdAjikQlruYyHV9lChoBkdAbs79kz41xmgHTTgBaAhHQI4pkMEzO5d1fZQoaAZHQHDZ2A9V3lloB00SAWgIR0COKd2LYPGydX2UKGgGR0Bw4k9W6shgaAdNDAFoCEdAjireeOGTLXV9lChoBkdAcsrG1hLGrGgHS/loCEdAjiyM90RvnHV9lChoBkdAcZuUSZjQRmgHS91oCEdAjiypKzzErHV9lChoBkdAczEOpbUwz2gHTT4BaAhHQI4ta5oXbdt1fZQoaAZHQHAgCCz1K5FoB0v4aAhHQI4t9zjm0Vt1fZQoaAZHQG+wBpYcNpdoB00EAWgIR0COLiETxoZidX2UKGgGR0ByMC/L1VYIaAdL+2gIR0COLiBvrGBGdX2UKGgGR0ByCz99+gDiaAdNFQFoCEdAji6jxTbWVnV9lChoBkdAcVo7aZhKDmgHS/hoCEdAjjBSncclxHV9lChoBkdAcB9ywwCbMGgHS/poCEdAjjNfaxoqTnV9lChoBkdAcaSA8SwnpmgHTa4BaAhHQI4zym65Gz91fZQoaAZHQHJybK/20zFoB00hAWgIR0CONWSQHRkVdX2UKGgGR0Bwp6g00m+kaAdNGQFoCEdAjjZ1AiV0LnV9lChoBkdAb4rQl8gIQmgHTQMBaAhHQI42fEZR8+l1fZQoaAZHQG20EgOjIq9oB00YAWgIR0COOAagElmfdX2UKGgGR0BzDwTDfm9yaAdNFwFoCEdAjjg98Aq/d3V9lChoBkdAci7naFmFrWgHTQ8BaAhHQI44yqwQlKN1fZQoaAZHQHC8/jwQUYdoB00LAWgIR0COOksEq2BrdX2UKGgGR0ByzCDrZ8KHaAdL82gIR0COOnh5xBE8dWUu"
|
| 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:": "gAWVdwIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBNudW1weS5fY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolggAAAAAAAAAAQEBAQEBAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUjAFDlHSUUpSMDWJvdW5kZWRfYWJvdmWUaBEolggAAAAAAAAAAQEBAQEBAQGUaBVLCIWUaBl0lFKUjAZfc2hhcGWUSwiFlIwDbG93lGgRKJYgAAAAAAAAAAAAtMIAALTCAACgwAAAoMDbD0nAAACgwAAAAIAAAACAlGgLSwiFlGgZdJRSlIwEaGlnaJRoESiWIAAAAAAAAAAAALRCAAC0QgAAoEAAAKBA2w9JQAAAoEAAAIA/AACAP5RoC0sIhZRoGXSUUpSMCGxvd19yZXBylIxbWy05MC4gICAgICAgIC05MC4gICAgICAgICAtNS4gICAgICAgICAtNS4gICAgICAgICAtMy4xNDE1OTI3ICAtNS4KICAtMC4gICAgICAgICAtMC4gICAgICAgXZSMCWhpZ2hfcmVwcpSMU1s5MC4gICAgICAgIDkwLiAgICAgICAgIDUuICAgICAgICAgNS4gICAgICAgICAzLjE0MTU5MjcgIDUuCiAgMS4gICAgICAgICAxLiAgICAgICBdlIwKX25wX3JhbmRvbZROdWIu",
|
| 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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
|
| 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:": "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"
|
| 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:f6919262a6711871fffe42b936531c7ee4bb87d4c86fd3cd9fd25e16970540c8
|
| 3 |
+
size 88695
|
ppo-LunarLander-v2/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2681bdff97e831479f3f9634dec4beee42e641041040f4e12990c5f71914f137
|
| 3 |
+
size 44095
|
ppo-LunarLander-v2/pytorch_variables.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:07c7431cf6005e7d8f367d79e995f63e2f9b981a37e3437b795d058f9af4308b
|
| 3 |
+
size 1261
|
ppo-LunarLander-v2/system_info.txt
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
- OS: Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025
|
| 2 |
+
- Python: 3.12.11
|
| 3 |
+
- Stable-Baselines3: 2.0.0a5
|
| 4 |
+
- PyTorch: 2.8.0+cu126
|
| 5 |
+
- GPU Enabled: True
|
| 6 |
+
- Numpy: 2.0.2
|
| 7 |
+
- Cloudpickle: 3.1.1
|
| 8 |
+
- Gymnasium: 0.28.1
|
| 9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d90714d4aa7c85a468cd343e396e9b570449fc992ae125b16f7a7a6997e55704
|
| 3 |
+
size 168088
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 263.6131191, "std_reward": 14.614909479348622, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-09-03T11:46:29.622481"}
|