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---
license: mit
library_name: pytorch
pipeline_tag: reinforcement-learning
language:
- en
tags:
- reinforcement-learning
- gymnasium
- CartPole-v1
- ppo
- pytorch
model-index:
- name: CartPole-v1_ppo
results:
- task:
type: reinforcement-learning
name: Reinforcement Learning
dataset:
name: CartPole-v1
type: gymnasium
metrics:
- name: Best Eval Reward
type: reward
value: 272.3999938964844
- name: Current Eval Reward
type: reward
value: 500.0
- name: Epoch
type: epoch
value: 199.0
- name: Total Timesteps
type: timesteps
value: 0.0
---
# CartPole-v1_ppo
Run: `cvb5lyfw` — Env: `CartPole-v1` — Algo: `ppo`
This repository contains artifacts from a Gymnasium Solver training run.
## Contents
- Config: `artifacts/configs/config.json`
- Checkpoints: `artifacts/checkpoints/*.ckpt`
- Logs: `artifacts/logs/*.log`
- Video: `artifacts/videos/**/best_checkpoint.mp4` (also previewed below)
## Preview
<video controls src="preview.mp4" width="480"></video>
If the video above doesn't load, try the fallback: [replay.mp4](replay.mp4)
## Config (excerpt)
```json
{
"env_id": "CartPole-v1",
"algo_id": "ppo",
"n_steps": 32,
"batch_size": 256,
"n_epochs": 20,
"n_timesteps": 100000.0,
"seed": 42,
"n_envs": 8,
"obs_type": "rgb",
"policy": "MlpPolicy",
"learning_rate": 0.001,
"gamma": 0.98,
"gae_lambda": 0.8,
"ent_coef": 0.0,
"vf_coef": 0.5,
"clip_range": 0.2,
"normalize_advantages": "batch"
}
``` |