nanoT5: Fast & Simple Pre-training and Fine-tuning of T5 Models with Limited Resources
Keywords: opensource, T5model, t5, pretraining, finetuning, efficient
TL;DR: A reproducible PyTorch repository for pre-training and fine-tuning of the T5 Language Models with Limited Resources
Abstract: State-of-the-art language models like T5 have revolutionized the NLP landscape, but their computational demands hinder a large portion of the research community. To address this challenge, we present nanoT5, a specially-optimized PyTorch framework for efficient pre-training and fine-tuning of T5 models. Drawing on insights from optimizer differences and prioritizing efficiency, nanoT5 allows a T5-Base model to be pre-trained on a single GPU in just 16 hours, without any loss in performance. With the introduction of this open-source framework, we hope to widen the accessibility to language modelling research and cater to the community's demand for more user-friendly T5 (Encoder-Decoder) implementations. We make our contributions, including configurations, codebase, pre-training insights, and pre-trained models, available to the public.
Submission Number: 18
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