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: 236.04 +/- 38.66
|
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 0x7966ee245cf0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7966ee245d80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7966ee245e10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7966ee245ea0>", "_build": "<function ActorCriticPolicy._build at 0x7966ee245f30>", "forward": "<function ActorCriticPolicy.forward at 0x7966ee245fc0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7966ee246050>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7966ee2460e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7966ee246170>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7966ee246200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7966ee246290>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7966ee246320>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7966f748c780>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1712568447515501361, "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:": "gAWVPgwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGBHf/m1YySMAWyUTegDjAF0lEdAlnC4yXUpeHV9lChoBkdAM+oy44Ia+GgHS+NoCEdAlnFut4iX6nV9lChoBkdAX2aecx0uDmgHTegDaAhHQJZxiRgZ0jl1fZQoaAZHQGJY8IzFdcBoB03oA2gIR0CWdVa/yoXLdX2UKGgGR0Bix2oxYaHcaAdN6ANoCEdAln7QpKBd2XV9lChoBkdAZJ1T987ZF2gHTegDaAhHQJaAkq6OHWV1fZQoaAZHQFx14M4LkS5oB03oA2gIR0CWhMFtsN2DdX2UKGgGR0Bej7hR64UfaAdN6ANoCEdAlofXxFy7w3V9lChoBkdAW4Ue/5+H8GgHTegDaAhHQJaLd3u/k/91fZQoaAZHQGTKr0z0pVloB03oA2gIR0CWjFtygf2cdX2UKGgGR0BIafM4cWCVaAdL62gIR0CWjr557gKndX2UKGgGR0Bl90L8aXKKaAdN6ANoCEdAlo9NYnv2G3V9lChoBkdAJBDj7yhBaGgHTQ8BaAhHQJaPn5VOsT51fZQoaAZHQGDsmlImPYFoB03oA2gIR0CWkhRzBAObdX2UKGgGR0BhN96Rhc7haAdN6ANoCEdAlpWmU4aP0nV9lChoBkdAZx+6+36RAGgHTegDaAhHQJaWcyhzvJB1fZQoaAZHQEB19x6v7nBoB0vzaAhHQJaqUj8k2P11fZQoaAZHQGMnhSk0rLBoB03oA2gIR0CWutAzHjp+dX2UKGgGR0Bm3OIuXeFdaAdN6ANoCEdAlr3aeXiR4nV9lChoBkdAXOFXeWOZLWgHTegDaAhHQJbB7ww0wal1fZQoaAZHQF/ctZV4oqloB03oA2gIR0CWwsczqKP5dX2UKGgGR0Bit4ZKnNxEaAdN6ANoCEdAlsLoNutOmHV9lChoBkdAWcmx1PnB+GgHTegDaAhHQJbHSTaCcwx1fZQoaAZHQGSv87p3X7NoB03oA2gIR0CW1gXq7iAEdX2UKGgGR0Bh2U7ZFocraAdN6ANoCEdAltl6z/p+t3V9lChoBkdAYiyGJvYOD2gHTegDaAhHQJbf4vugHu91fZQoaAZHQGKenuAqd6NoB03oA2gIR0CW4uB8hLXddX2UKGgGR0BakkfHPu5SaAdN6ANoCEdAluNr6LwWnHV9lChoBkdAYXuCwKSgXmgHTegDaAhHQJbjvwAlv611fZQoaAZHQGIb2Af+0gNoB03oA2gIR0CW5fpjMFEBdX2UKGgGR0BA0AiV0Lc9aAdL7mgIR0CW6JQHiWE9dX2UKGgGR0Bh2X8fms/6aAdN6ANoCEdAluktSVGCqnV9lChoBkdAXY2+PBBRh2gHTegDaAhHQJbp36+FlCl1fZQoaAZHQFitKCg9NetoB03oA2gIR0CW62CnP3SKdX2UKGgGR0BoMwfW+XZ5aAdN6ANoCEdAlwjxlMAWBXV9lChoBkdAXwRdld1Md2gHTegDaAhHQJcMNUHY6GR1fZQoaAZHQGCMXcQAdXFoB03oA2gIR0CXELdz4k/sdX2UKGgGR0BhEy5TZQHiaAdN6ANoCEdAlxGz+vQnhXV9lChoBkdAZggOS4e9z2gHTegDaAhHQJcR2MOwxFl1fZQoaAZHQGNI1zQu27ZoB03oA2gIR0CXFXc/t6X0dX2UKGgGR0Bvw62x6fJ4aAdNkQJoCEdAlx9+mvW6LHV9lChoBkdAYWXk078vVWgHTegDaAhHQJch+RDCxeN1fZQoaAZHQGJ0ZFgDzRRoB03oA2gIR0CXKc1R+BpYdX2UKGgGR0BjklV1fVqfaAdN6ANoCEdAlyxYHX2/SHV9lChoBkdAXNrJfYzzmWgHTegDaAhHQJctAqbz9TB1fZQoaAZHQGBCETQE6ktoB03oA2gIR0CXLVz2OAAidX2UKGgGR0BjTl9roGILaAdN6ANoCEdAly/5RoAXEnV9lChoBkdAYu+NyYG+smgHTegDaAhHQJczPIDHOr11fZQoaAZHQGTOTG5tm+VoB03oA2gIR0CXNMjFhodudX2UKGgGR0BiOhGrjo6kaAdN6ANoCEdAlzbG7OE/S3V9lChoBkdASRbPldTo+2gHS/ZoCEdAl1fOE7GNrHV9lChoBkdAZDEhh6SkkGgHTegDaAhHQJdZclSjxkN1fZQoaAZHQGBhUzTF2mpoB03oA2gIR0CXXGIyTINmdX2UKGgGR0BnJ7Yf4h2XaAdN6ANoCEdAl1/ypaRp13V9lChoBkdAYmnaC+UQkGgHTegDaAhHQJdgqSdOIqN1fZQoaAZHQGJhcg6ltTFoB03oA2gIR0CXYMjlgc94dX2UKGgGR0BkT4uqWC2+aAdN6ANoCEdAl2RRuKoAGXV9lChoBkdAYj0dbPhQ32gHTegDaAhHQJdwp8Yyfth1fZQoaAZHQGKEVQIldC5oB03oA2gIR0CXcynRLK3edX2UKGgGR0BjXEaQ3gk1aAdN6ANoCEdAl3ruFlCkXXV9lChoBkdAYN/6O5rgwWgHTegDaAhHQJd9N7gKnel1fZQoaAZHQGX8MqJ/G2loB03oA2gIR0CXfcR/3FkydX2UKGgGR0BhW0uQIUrTaAdN6ANoCEdAl34XVLBbfXV9lChoBkdAXW9GiHqNZWgHTegDaAhHQJeAi1rqMWJ1fZQoaAZHQGMWSZrpJPJoB03oA2gIR0CXg3ZoPCl8dX2UKGgGR0Bl0MD+zdDZaAdN6ANoCEdAl4aNOqNp/XV9lChoBkdAXdwLkS26TWgHTegDaAhHQJelvefqX4V1fZQoaAZHQGHrUpmVZ9xoB03oA2gIR0CXpxsqaw2VdX2UKGgGR0Bl9tDBuXNUaAdN6ANoCEdAl6mP6wdKd3V9lChoBkdAbtjAbADaG2gHTcUBaAhHQJesjxd6cAl1fZQoaAZHQGM7i4SYgJVoB03oA2gIR0CXrMc+aBqcdX2UKGgGR0Blbz8m8dxRaAdN6ANoCEdAl61wbuMMqnV9lChoBkdAZG282aUiZGgHTegDaAhHQJetiDoQnQZ1fZQoaAZHQGI5FCCz1K5oB03oA2gIR0CXsNNi6QNkdX2UKGgGR0BlP6brkbPyaAdN6ANoCEdAl7rNCmdiD3V9lChoBkdAY6gez2OAAmgHTegDaAhHQJe9F3Roh6l1fZQoaAZHQGS/0SZjQRhoB03oA2gIR0CXxRoWYWtVdX2UKGgGR0BgmlOXVsk6aAdN6ANoCEdAl8e7EUCaJHV9lChoBkdAYpFCiyprDmgHTegDaAhHQJfIUSoOx0N1fZQoaAZHQGN8HUc4o7VoB03oA2gIR0CXyKYIjW07dX2UKGgGR0BmLPuLJjlQaAdN6ANoCEdAl9A7LMcIaHV9lChoBkdAZav8Q7LdN2gHTegDaAhHQJfUI6nzg/F1fZQoaAZHQDHSEi+tbLVoB0vYaAhHQJfWTwqiGnJ1fZQoaAZHQG+6FkYoAn5oB00NAmgIR0CX7YnqFAVxdX2UKGgGR0BjWz987ZFoaAdN6ANoCEdAl/H1NUOuq3V9lChoBkdAYlA4Wk8A72gHTegDaAhHQJfzOq+8Gs51fZQoaAZHQGdjLW7OE/VoB03oA2gIR0CX9XJ66asqdX2UKGgGR0Bhz5g3Lmp3aAdN6ANoCEdAl/g5vDP4VXV9lChoBkdAYSF2TxG2C2gHTegDaAhHQJf4bOhTOxB1fZQoaAZHQGPh2hRIjGFoB03oA2gIR0CX+RjqfOD8dX2UKGgGR0Bi+Y+4b0e2aAdN6ANoCEdAl/k5CF9KEnV9lChoBkdAZbUFB6a9b2gHTegDaAhHQJf9mgdwNsp1fZQoaAZHQG4u6a9bor5oB03VAWgIR0CYAVPD50r9dX2UKGgGR0BfthIatLcsaAdN6ANoCEdAmAq9/e+EiHV9lChoBkdAZArFVDKHPGgHTegDaAhHQJgSJl5GBnV1fZQoaAZHQGAtGfoRqXZoB03oA2gIR0CYFH580DU3dX2UKGgGR0Bh+UlzEJjUaAdN6ANoCEdAmBViT2WY4XV9lChoBkdAaBaOaOPvKGgHTegDaAhHQJgatwQ176Z1fZQoaAZHQHFvObExZdRoB02FAmgIR0CYHQlhgE2YdX2UKGgGR0BhD96kZaV2aAdN6ANoCEdAmCBP8AJb+3VlLg=="}, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "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 sha256:6a2af6581f75e1e38da206620c54b56cbe7c0d4fd1c7d4430d4e06c2a2c82c49
|
3 |
+
size 148080
|
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 0x7966ee245cf0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7966ee245d80>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7966ee245e10>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7966ee245ea0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7966ee245f30>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7966ee245fc0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7966ee246050>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7966ee2460e0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7966ee246170>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7966ee246200>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7966ee246290>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7966ee246320>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7966f748c780>"
|
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": 1712568447515501361,
|
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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
|
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 sha256:8f0ba69bb7eb29cbe25734f6e0fd52845bce17de424a7dcb0f1138ad9280591f
|
3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:59ad626a70e34a5cb29aa676e171efe7ff84aa9a3891ef425ff0ec6f3f84fb5c
|
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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.2.1+cu121
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.25.2
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
Binary file (182 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 236.03959875474783, "std_reward": 38.65831347961434, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-08T09:53:58.732231"}
|