Train LunarLander
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: 240.26 +/- 17.43
|
| 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 0x7c2744d65ea0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c2744d65f30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c2744d65fc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c2744d66050>", "_build": "<function ActorCriticPolicy._build at 0x7c2744d660e0>", "forward": "<function ActorCriticPolicy.forward at 0x7c2744d66170>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c2744d66200>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c2744d66290>", "_predict": "<function ActorCriticPolicy._predict at 0x7c2744d66320>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c2744d663b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c2744d66440>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c2744d664d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c2744d6cd00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1746871650908781382, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlgAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAACaNYs9+FyVPAq9FT1zNQ++HAwRvL9dEDwAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksBhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3908, "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, "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": "Generator(PCG64)"}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.11.0-25-generic-x86_64-with-glibc2.39 # 25~24.04.1-Ubuntu SMP PREEMPT_DYNAMIC Tue Apr 15 17:20:50 UTC 2", "Python": "3.10.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.7.0+cu126", "GPU Enabled": "True", "Numpy": "2.2.5", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI 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:aa06d6f1e2b919585f960ba14d148c354f66aafcff5c3ad180bf3ddc97a741d2
|
| 3 |
+
size 150019
|
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 0x7c2744d65ea0>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c2744d65f30>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c2744d65fc0>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c2744d66050>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7c2744d660e0>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7c2744d66170>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7c2744d66200>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c2744d66290>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7c2744d66320>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c2744d663b0>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c2744d66440>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7c2744d664d0>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7c2744d6cd00>"
|
| 21 |
+
},
|
| 22 |
+
"verbose": 1,
|
| 23 |
+
"policy_kwargs": {},
|
| 24 |
+
"num_timesteps": 1000448,
|
| 25 |
+
"_total_timesteps": 1000000,
|
| 26 |
+
"_num_timesteps_at_start": 0,
|
| 27 |
+
"seed": null,
|
| 28 |
+
"action_noise": null,
|
| 29 |
+
"start_time": 1746871650908781382,
|
| 30 |
+
"learning_rate": 0.0003,
|
| 31 |
+
"tensorboard_log": null,
|
| 32 |
+
"_last_obs": {
|
| 33 |
+
":type:": "<class 'numpy.ndarray'>",
|
| 34 |
+
":serialized:": "gAWVlgAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAACaNYs9+FyVPAq9FT1zNQ++HAwRvL9dEDwAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsIhpSMAUOUdJRSlC4="
|
| 35 |
+
},
|
| 36 |
+
"_last_episode_starts": {
|
| 37 |
+
":type:": "<class 'numpy.ndarray'>",
|
| 38 |
+
":serialized:": "gAWVdQAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksBhZSMAUOUdJRSlC4="
|
| 39 |
+
},
|
| 40 |
+
"_last_original_obs": null,
|
| 41 |
+
"_episode_num": 0,
|
| 42 |
+
"use_sde": false,
|
| 43 |
+
"sde_sample_freq": -1,
|
| 44 |
+
"_current_progress_remaining": -0.00044800000000000395,
|
| 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": 3908,
|
| 55 |
+
"n_steps": 1024,
|
| 56 |
+
"gamma": 0.999,
|
| 57 |
+
"gae_lambda": 0.98,
|
| 58 |
+
"ent_coef": 0.01,
|
| 59 |
+
"vf_coef": 0.5,
|
| 60 |
+
"max_grad_norm": 0.5,
|
| 61 |
+
"batch_size": 64,
|
| 62 |
+
"n_epochs": 4,
|
| 63 |
+
"clip_range": {
|
| 64 |
+
":type:": "<class 'function'>",
|
| 65 |
+
":serialized:": "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"
|
| 66 |
+
},
|
| 67 |
+
"clip_range_vf": null,
|
| 68 |
+
"normalize_advantage": true,
|
| 69 |
+
"target_kl": null,
|
| 70 |
+
"observation_space": {
|
| 71 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
| 72 |
+
":serialized:": "gAWVGQQAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBNudW1weS5fY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolggAAAAAAAAAAQEBAQEBAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUjAFDlHSUUpSMDWJvdW5kZWRfYWJvdmWUaBEolggAAAAAAAAAAQEBAQEBAQGUaBVLCIWUaBl0lFKUjAZfc2hhcGWUSwiFlIwDbG93lGgRKJYgAAAAAAAAAAAAtMIAALTCAACgwAAAoMDbD0nAAACgwAAAAIAAAACAlGgLSwiFlGgZdJRSlIwEaGlnaJRoESiWIAAAAAAAAAAAALRCAAC0QgAAoEAAAKBA2w9JQAAAoEAAAIA/AACAP5RoC0sIhZRoGXSUUpSMCGxvd19yZXBylIxbWy05MC4gICAgICAgIC05MC4gICAgICAgICAtNS4gICAgICAgICAtNS4gICAgICAgICAtMy4xNDE1OTI3ICAtNS4KICAtMC4gICAgICAgICAtMC4gICAgICAgXZSMCWhpZ2hfcmVwcpSMU1s5MC4gICAgICAgIDkwLiAgICAgICAgIDUuICAgICAgICAgNS4gICAgICAgICAzLjE0MTU5MjcgIDUuCiAgMS4gICAgICAgICAxLiAgICAgICBdlIwKX25wX3JhbmRvbZSMFG51bXB5LnJhbmRvbS5fcGlja2xllIwQX19nZW5lcmF0b3JfY3RvcpSTlGgyjBRfX2JpdF9nZW5lcmF0b3JfY3RvcpSTlIwTbnVtcHkucmFuZG9tLl9wY2c2NJSMBVBDRzY0lJOUhZRSlH2UKIwNYml0X2dlbmVyYXRvcpSMBVBDRzY0lIwFc3RhdGWUfZQoaD+KEG0+9ak0Vz2OKeL4Uc8hjS+MA2luY5SKEKeuFFs8JSc/4ACOQF80Nl11jApoYXNfdWludDMylEsAjAh1aW50ZWdlcpRLAHWMGm51bXB5LnJhbmRvbS5iaXRfZ2VuZXJhdG9ylIwbX19weXhfdW5waWNrbGVfU2VlZFNlcXVlbmNllJOUaESMDFNlZWRTZXF1ZW5jZZSTlEoiouoDToeUUpQoihHvKIb39Sj2oMSteyo/oG3cAEsAaBEolhAAAAAAAAAA8poywk1UOfl8uqhwAIFAh5RoCIwCdTSUiYiHlFKUKEsDaAxOTk5K/////0r/////SwB0lGJLBIWUaBl0lFKUSwQpdJRihpRihZRSlHViLg==",
|
| 73 |
+
"dtype": "float32",
|
| 74 |
+
"bounded_below": "[ True True True True True True True True]",
|
| 75 |
+
"bounded_above": "[ True True True True True True True True]",
|
| 76 |
+
"_shape": [
|
| 77 |
+
8
|
| 78 |
+
],
|
| 79 |
+
"low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
| 80 |
+
"high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
| 81 |
+
"low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
| 82 |
+
"high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
| 83 |
+
"_np_random": "Generator(PCG64)"
|
| 84 |
+
},
|
| 85 |
+
"action_space": {
|
| 86 |
+
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
| 87 |
+
":serialized:": "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",
|
| 88 |
+
"n": "4",
|
| 89 |
+
"start": "0",
|
| 90 |
+
"_shape": [],
|
| 91 |
+
"dtype": "int64",
|
| 92 |
+
"_np_random": "Generator(PCG64)"
|
| 93 |
+
},
|
| 94 |
+
"n_envs": 1,
|
| 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 sha256:477e188ad9584d5f58825986576b7bba1a3e8966a58398506dd1129b41cbcfa4
|
| 3 |
+
size 88887
|
ppo-LunarLander-v2/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:975af1b73038eca2cfe1078ccb2e61a1e97fc7b3d66c6c36b3188e158042b0d5
|
| 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-6.11.0-25-generic-x86_64-with-glibc2.39 # 25~24.04.1-Ubuntu SMP PREEMPT_DYNAMIC Tue Apr 15 17:20:50 UTC 2
|
| 2 |
+
- Python: 3.10.13
|
| 3 |
+
- Stable-Baselines3: 2.0.0a5
|
| 4 |
+
- PyTorch: 2.7.0+cu126
|
| 5 |
+
- GPU Enabled: True
|
| 6 |
+
- Numpy: 2.2.5
|
| 7 |
+
- Cloudpickle: 3.1.1
|
| 8 |
+
- Gymnasium: 0.28.1
|
| 9 |
+
- OpenAI Gym: 0.21.0
|
replay.mp4
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6f039a58703c2dd4c40abde0de295a82c8b6f229e70314ea44e1aa293b41ebc2
|
| 3 |
+
size 146561
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 240.26450979999998, "std_reward": 17.426798491134992, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-05-10T16:56:28.204944"}
|