Fine tune a T5 transformer model using PyTorch & Transformers🤗 - Shivanandroy/T5-Finetuning-PyTorch

Recently, I am running an NLP-related (secretive lol) project, which needs to fine-tune a T5 model. I look around the fine-tune script through Chinese communities however can't find a good doc for T5 fine-tuning.

2022年5月17日 · In this article, we chose a suitable dataset and metric for our title generation task, and we wrote some code with the Hugging Face library to fine-tune a pre-trained T5 model for our task.

本代码实现了在BoolQ数据集上，使用T5模型微调预测答案得功能。支持得微调主要包括： Fine Tuning T5模型Decoder最后两层，也即轻量级微调. Prompt Tuning，在输入X前加入soft prompt：

The PAD token is hereby used as the start-sequence token. T5 can be trained / fine-tuned both in a supervised and unsupervised fashion. One can use T5ForConditionalGeneration (or the Tensorflow/Flax variant), which includes the language modeling head on top of the decoder. Unsupervised denoising training

2023年10月22日 · Text-To-Text Transfer Transformer (T5) is a pre-trained encoder-decoder model handling all NLP tasks as a unified text-to-text-format where the input and...

A simple example for finetuning HuggingFace T5 model. Includes code for intermediate generation.

T5 is an encoder-decoder model pre-trained on a multi-task mixture of unsupervised and supervised tasks and for which each task is converted into a text-to-text format.

2022年3月27日 · 最近的一个项目需要用到T5模型。众所周知，就跟拓海AE86的11000转一样，T5模型不上到3 Billion的参数规模，效果(大概率)是干不过其他Encoder-only的模型的。 但是实验室的A100/V100们常年满负荷工作，基本找不到能火力全开的时候。

2023年1月5日 · In this blog, we will explore how to fine-tune T5 for text generation and demonstrate the results with a few examples. We will also discuss some best practices and considerations when...