all AI news
Scaling Instruction-Finetuned Language Models. (arXiv:2210.11416v4 [cs.LG] UPDATED)
Nov. 24, 2022, 7:18 a.m. | Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webs
cs.CL updates on arXiv.org arxiv.org
Finetuning language models on a collection of datasets phrased as
instructions has been shown to improve model performance and generalization to
unseen tasks. In this paper we explore instruction finetuning with a particular
focus on (1) scaling the number of tasks, (2) scaling the model size, and (3)
finetuning on chain-of-thought data. We find that instruction finetuning with
the above aspects dramatically improves performance on a variety of model
classes (PaLM, T5, U-PaLM), prompting setups (zero-shot, few-shot, CoT), and
evaluation …
More from arxiv.org / cs.CL updates on arXiv.org
Jobs in AI, ML, Big Data
Senior ML Researcher - 3D Geometry Processing | 3D Shape Generation | 3D Mesh Data
@ Promaton | Europe
Principal Data Engineer
@ RS21 | Remote
SQL/Power BI Developer
@ ICF | Virginia Remote Office (VA99)
Senior Machine Learning Engineer (Canada Remote)
@ Fullscript | Ottawa, ON
Software Engineer - MLOps.
@ Renesas Electronics | Toyosu, Japan
Junior Data Scientist / Artificial Intelligence consultant
@ Deloitte | Luxembourg, LU