我们的工作涉及到广泛的领域,如zero-shot learning, prompting, multi-task learning, and language models for NLP applications。 Section 6. Discussion 本文探索了一个关于zero-shot prompting的简单问题:在instruction形式的数据上微调模型,对于未见过任务是否具备泛化性?我们采用了Instruction tuning,一种结合pretrain...
对每个数据集的十个模板进行测试，求出平均值和标准差，代表自然语言指令预期性能的典型结果。比较LaMDA-PT的zero-shot和few-shot结果，FLAN在25个数据集中的20个任务上超越了GPT-3。同时，FLAN在10个数据集上优于few-shot GPT-3，在GLaM上也有类似效果。核心实验研究instruction tuning如何提升模型对unse...
论文解读:Finetuned Language Models Are Zero-shot Learners 简要信息: 一、概念: Instruction-tuning——finetuning language models on a collection of tasks (more than 60 NLP tasks) described via instructions 本文提出一种基于instruction-tuning的方法叫做FLAN(Finetuned LAnguage Net) 评估方法:对所...
This paper explores a simple method for improving the zero-shot learning abilities of language models. We show that instruction tuning -- finetuning language models on a collection of tasks described via instructions -- substantially improves zero-shot performance on unseen tasks. We take a 137B ...
Finetuned Language Models Are Zero-Shot LearnersJason WeiMaarten BosmaVincent Y. ZhaoKelvin GuuAdams Wei YuBrian LesterNan DuAndrew M. DaiQuoc V. Le
Le. 2022. Finetuned language models are zero-shot learners. In Proc. of ICLR. Williams et al. (2018) Adina Williams, Nikita Nangia, and Samuel Bowman. 2018. A broad-coverage challenge corpus for sentence understanding through inference. In Proc. of NAACL. Yang et al. (2018) ...
For that, we can view the hf-speech-bench, a leaderboard that categorises models by language and dataset, and subsequently ranks them according to their WER. Our fine-tuned model significantly improves upon the zero-shot performance of the Whisper small checkpoint, highlighting the st...
Zero-shot example: Training Eval results languagetagslicensedatasetsmetrics multilingualenfresdeelbgrutrarvithzhhiswur pytorch apache-2.0 multi_nlixnli xnli mt5-large-finetuned-mnli-xtreme-xnli Model Description This model takes a pretrained largemultilingual-t5(also available frommodels) and fine-tunes...
large-language-models.md lewis-tunstall-interview.md long-range-transformers.md meg-mitchell-interview.md ml-director-insights.md opinion-classification-with-kili.md perceiver.md porting-fsmt.md pytorch-fsdp.md pytorch-xla.md pytorch_block_sparse.md ray-rag.md ray-tune.md reformer...
Instruction-tuning:仍然在预训练语言模型的基础上,先在多个已知任务上进行微调(通过自然语言的形式),然后再推理某个新任务上进行zero-shot 论文动机: 大规模语言模型(如GPT-3)在小样本学习方面表现出色,但零样本学习表现较差。这限制了这些模型的应用范围