تقرير
Fast Optimizer Benchmark
| العنوان: | Fast Optimizer Benchmark |
|---|---|
| المؤلفون: | Blauth, Simon, Bürger, Tobias, Häringer, Zacharias, Franke, Jörg, Hutter, Frank |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Machine Learning, Computer Science - Artificial Intelligence |
| الوصف: | In this paper, we present the Fast Optimizer Benchmark (FOB), a tool designed for evaluating deep learning optimizers during their development. The benchmark supports tasks from multiple domains such as computer vision, natural language processing, and graph learning. The focus is on convenient usage, featuring human-readable YAML configurations, SLURM integration, and plotting utilities. FOB can be used together with existing hyperparameter optimization (HPO) tools as it handles training and resuming of runs. The modular design enables integration into custom pipelines, using it simply as a collection of tasks. We showcase an optimizer comparison as a usage example of our tool. FOB can be found on GitHub: https://github.com/automl/FOBTest. Comment: 5 pages + 12 appendix pages, submitted to AutoML Conf 2024 Workshop Track |
| نوع الوثيقة: | Working Paper |
| الوصول الحر: | http://arxiv.org/abs/2406.18701Test |
| رقم الانضمام: | edsarx.2406.18701 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |