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: 277.63 +/- 16.34
|
| 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 0x7d72a8021480>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d72a8021510>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d72a80215a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d72a8021630>", "_build": "<function ActorCriticPolicy._build at 0x7d72a80216c0>", "forward": "<function ActorCriticPolicy.forward at 0x7d72a8021750>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d72a80217e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d72a8021870>", "_predict": "<function ActorCriticPolicy._predict at 0x7d72a8021900>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d72a8021990>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d72a8021a20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d72a8021ab0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d72a8024440>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1700251633344747023, "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": 785, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-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": "2.1.0+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 sha256:7f9e89190e1efc8ef0f7062a2dd5eba56d61369ae48fa1a77c975170f59779b6
|
| 3 |
+
size 147921
|
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 0x7d72a8021480>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d72a8021510>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d72a80215a0>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d72a8021630>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7d72a80216c0>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7d72a8021750>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7d72a80217e0>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d72a8021870>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7d72a8021900>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d72a8021990>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d72a8021a20>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7d72a8021ab0>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7d72a8024440>"
|
| 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": 1700251633344747023,
|
| 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:": "gAWV4AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHK22CiAUcqMAWyUS7GMAXSUR0C0U2yzLOiWdX2UKGgGR0BwJ5Fx4ptraAdLmmgIR0C0U4pKnNxEdX2UKGgGR0BzS7u1F6RhaAdLtGgIR0C0U5bTc6/7dX2UKGgGR0BwynWBjFyaaAdLo2gIR0C0U5p7kXDWdX2UKGgGR0BxomvbGm1qaAdLvWgIR0C0U7FglWwNdX2UKGgGR0BysBATqSowaAdLkmgIR0C0U7RJ7LMcdX2UKGgGR0BxK6weNkvsaAdLtGgIR0C0U7QvtdAxdX2UKGgGR0Bwado6CDmKaAdLnmgIR0C0U86Ezwc6dX2UKGgGR0BzEcMI/qxDaAdL/mgIR0C0U9HEQ5FPdX2UKGgGR0Bv5vZf2K2saAdLmWgIR0C0U9mdmQKbdX2UKGgGR0ByigzpHI6saAdLwmgIR0C0U9eIEbHZdX2UKGgGR0BwlONlyzX0aAdLumgIR0C0U+nFkxyodX2UKGgGR0Bx8hZEDyOJaAdLxmgIR0C0U++eOGTLdX2UKGgGR0Bwqs0FbFCLaAdLk2gIR0C0U/VIVdondX2UKGgGR0BuGDaCcwxnaAdLmmgIR0C0VBDGcWj5dX2UKGgGR0Byl+9rXUYsaAdLumgIR0C0VCHenAIqdX2UKGgGR0ByPjbVSXMRaAdLy2gIR0C0VGgcT8HfdX2UKGgGR0BxYD/6wdKeaAdLtWgIR0C0VHbr9l3AdX2UKGgGR0BxvkEidJ8OaAdLu2gIR0C0VII150KadX2UKGgGR0BzYoIjW07baAdLzGgIR0C0VIgqVhTgdX2UKGgGR0BwzQg9vCMxaAdLt2gIR0C0VJltKqXGdX2UKGgGR0BvqeIAOrhjaAdLnmgIR0C0VJ6GHpKSdX2UKGgGR0By4Hj7yhBaaAdLw2gIR0C0VKaW5YozdX2UKGgGR0BwxTxri2lVaAdLkGgIR0C0VKhujynUdX2UKGgGR0Bywvu5SWJKaAdLvWgIR0C0VMIIrvsrdX2UKGgGR0Bz9yjxkNF0aAdL2mgIR0C0VMmqkuYhdX2UKGgGR0BxUxljEvTPaAdLxWgIR0C0VNaLfk3kdX2UKGgGR0BzDaQU5+6RaAdL0GgIR0C0VNjErGzbdX2UKGgGR0BxkcClrM1TaAdLvWgIR0C0VN3XZoPDdX2UKGgGR0B0Ax/8VHnVaAdLvGgIR0C0VOulXRw7dX2UKGgGR0ByGiVPepGXaAdLi2gIR0C0VShVdX1bdX2UKGgGR0ByrSWzF+/haAdL02gIR0C0VTHPu5SWdX2UKGgGR0ByyYxi5NGmaAdLkmgIR0C0VUI0dilSdX2UKGgGR0BzVxWilBQfaAdLpmgIR0C0VW5r+HafdX2UKGgGR0Bw0Gt7rs0IaAdLl2gIR0C0VXmJN0vHdX2UKGgGR0Byx7yqdYnwaAdLvWgIR0C0VYirtE5RdX2UKGgGR0ByF/w8W9DhaAdLsWgIR0C0VY+4oZyddX2UKGgGR0ByJ+JUHY6GaAdLtWgIR0C0VaMsxwhodX2UKGgGR0BvP9FnZkCnaAdLlmgIR0C0Va2KQ7tBdX2UKGgGR0ByMC/VRUFTaAdLpGgIR0C0VawnYxtYdX2UKGgGR0BxORqBVdX1aAdLzmgIR0C0VbrwWnCPdX2UKGgGR0BxoiQIUrTZaAdLn2gIR0C0VcdGI9DAdX2UKGgGR0ByjxPEbYK6aAdLzWgIR0C0VdrSZ0CBdX2UKGgGR0By3ee8PFvRaAdLv2gIR0C0Vd4+bExZdX2UKGgGR0Bu/UEidJ8OaAdLmGgIR0C0VfSCWeH0dX2UKGgGR0BznZcfNiYtaAdL1WgIR0C0VfhgJC0GdX2UKGgGR0BxNIhKUVzqaAdLpWgIR0C0Vhpk078vdX2UKGgGR0BysUvzvqkeaAdLsmgIR0C0Vhy+Yc//dX2UKGgGR0BxNO5kK/mDaAdLpGgIR0C0VlIsVclgdX2UKGgGR0ByQ0x9G7SRaAdLw2gIR0C0VoP4mCyydX2UKGgGR0ByZkku6ErYaAdLn2gIR0C0Voy2DxsmdX2UKGgGR0BzHr+glF+eaAdLmGgIR0C0VqFwgkkbdX2UKGgGR0ByaGInBtUGaAdLy2gIR0C0Vr15Sm65dX2UKGgGR0ByH7H93r2QaAdLsWgIR0C0VsFkpZwGdX2UKGgGR0Bxf+k8A7xNaAdLtWgIR0C0VsijQAuJdX2UKGgGR0BwZ0xfv4M4aAdLkWgIR0C0VszAvcrRdX2UKGgGR0ByQUo7V8TjaAdLz2gIR0C0VtE+cH4XdX2UKGgGR0Bxg0JrtVrAaAdLvWgIR0C0VvmY8dPtdX2UKGgGR0Byn8b3oLXuaAdLl2gIR0C0VyiR8twrdX2UKGgGR0BxDawV0tAcaAdLtWgIR0C0Vy2V3Ux3dX2UKGgGR0By2pMj/uLKaAdLmmgIR0C0VzMtsenydX2UKGgGR0ByMBXo1UEQaAdLyGgIR0C0V1GLUCq7dX2UKGgGR0By7Bg0CRwIaAdL4GgIR0C0V1nqJMxodX2UKGgGR0Bx2q4x1xKhaAdLjmgIR0C0V5wRf4RFdX2UKGgGR0BvNtBKL877aAdLmWgIR0C0V6lefI0ZdX2UKGgGR0ByPFYzSCvpaAdLiGgIR0C0V7+y/sVtdX2UKGgGR0BwdL/82rGSaAdLl2gIR0C0V+wCKaXsdX2UKGgGR0BxocEW69TQaAdL12gIR0C0V/VZs9B9dX2UKGgGR0BzE6LHdXT3aAdLumgIR0C0WAUmUnogdX2UKGgGR0BzF2E/SpiraAdLrWgIR0C0WBNtuUD/dX2UKGgGR0BxSJ1xKg7HaAdLkmgIR0C0WBNB8hLXdX2UKGgGR0BxvueFtbcHaAdLwWgIR0C0WDR3qzJIdX2UKGgGR0BynwgDA8B/aAdLmGgIR0C0WE7JW/8EdX2UKGgGR0BxtyNwR5C4aAdLgmgIR0C0WFE+C9RKdX2UKGgGR0ByjQ5QxesxaAdL2GgIR0C0WFZwXIludX2UKGgGR0Bxv22VmjCYaAdLsWgIR0C0WIWlhw2mdX2UKGgGR0Bx1n3YcvM9aAdLkmgIR0C0WL32mHgxdX2UKGgGR0BzALpNbkfcaAdL02gIR0C0WMKBd2PldX2UKGgGR0ByyjVSXMQmaAdLxmgIR0C0WMlGXokidX2UKGgGR0BxqlRVIZqEaAdLgmgIR0C0WOBgZ0jkdX2UKGgGR0BwmdR51Ng0aAdLjGgIR0C0WRZpnHvMdX2UKGgGR0ByPSaqjrRjaAdLzGgIR0C0WRuXAuZkdX2UKGgGR0Bxd+POpsGgaAdLkWgIR0C0WSArUb1idX2UKGgGR0Bu1mAd4mkWaAdLjGgIR0C0WTZPykKvdX2UKGgGR0ByWQoZydWiaAdLzGgIR0C0WT0EcKgJdX2UKGgGR0ByCWVPepGXaAdLuGgIR0C0WUg9vCMxdX2UKGgGR0By6Rxeb/fgaAdL0WgIR0C0WYdjPOY6dX2UKGgGR0BxG25Zr56/aAdLpmgIR0C0WYfcJtzkdX2UKGgGR0BwqKhdt2s8aAdLpGgIR0C0WbgmNR3vdX2UKGgGR0By3INKAavSaAdLyGgIR0C0WcRl18sudX2UKGgGR0BzzyFmFrVOaAdLz2gIR0C0WdUaQ3gldX2UKGgGR0Bv+h4nndO7aAdLmWgIR0C0Wehkd3jddX2UKGgGR0By5zDLr5ZbaAdLs2gIR0C0WhK9kBjndX2UKGgGR0BzT3L/0dzXaAdLo2gIR0C0WhMifQKKdX2UKGgGR0Bxwq+Jxeb/aAdLxGgIR0C0Wi16mfoSdX2UKGgGR0BzfIfIS13MaAdLoGgIR0C0WkwdwNsndX2UKGgGR0Bx3nFsHjZMaAdLk2gIR0C0WmaJdjXndX2UKGgGR0BzsPRMN+b3aAdLr2gIR0C0WmW65Gz9dX2UKGgGR0BxDff51vETaAdLrGgIR0C0Wo34O+ZgdX2UKGgGR0Bx5vVDrqt6aAdLt2gIR0C0Wpz+JgstdWUu"
|
| 49 |
+
},
|
| 50 |
+
"ep_success_buffer": {
|
| 51 |
+
":type:": "<class 'collections.deque'>",
|
| 52 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
| 53 |
+
},
|
| 54 |
+
"_n_updates": 785,
|
| 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": 2048,
|
| 81 |
+
"gamma": 0.99,
|
| 82 |
+
"gae_lambda": 0.95,
|
| 83 |
+
"ent_coef": 0.0,
|
| 84 |
+
"vf_coef": 0.5,
|
| 85 |
+
"max_grad_norm": 0.5,
|
| 86 |
+
"batch_size": 64,
|
| 87 |
+
"n_epochs": 10,
|
| 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 sha256:61f9d6afeba8aa8d70ac24146c8b95a834fb7d2dc56892048de92fa7897f9d2a
|
| 3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ba58ef1547281c786674bccac0e7714ff6460956416c5c40ee38d0f6d6e98aa7
|
| 3 |
+
size 43762
|
ppo-LunarLander-v2/pytorch_variables.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
|
| 3 |
+
size 864
|
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: 2.1.0+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 (165 kB). View file
|
|
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 277.6340905, "std_reward": 16.336138234519556, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-17T20:36:01.928953"}
|