Deep Dive Into Text2Text Feedback Datasets with QA Translation and Summarisation Templates

Gen1 Text2Text datasets in argilla makes the annotation of Text Datasets very easy. Gen2 make it more streamlined, and provides opportunities to further automate the Dataset creation, annotation, followed by extracting the response from the dataset.
We will dive into Summarisation, QA and Translation Feedback Dataset templates. And see how the render on the Argilla Server.
Chapter Navigation:
0:00 Intro
0:20 Purpose of Text2Text DS
0:45 Text2Text Tasks in NLP
2:25 How Text Generation Model is Trained
5:10 Connecting to Argilla Server
5:50 Gen1 Text2Text Dataset
6:40 Annotation with Gen1 Text2Text DS
7:40 Annotating with JSON Output Text
9:25 Intro to Feedback Dataset Templates
11:10 Recap of FeedBack Dataset Parts
11:55 Intro Summarisation Template in FB Dataset
15:35 Annotating FB Dataset in Argilla Server
17:45 Translation Task FB Dataset Instantiation
20:10 Annotating With Translation FB Dataset
20:55 Question Answer Task FB Dataset Instantiation
22:30 Annotating with QA feedback Dataset
23:10 Recap
24:50 Outro
The data and the code is located at
github.com/insightbuilder/pyt...
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