T5 Small Squad Qg

🚀 Model Card of lmqg/t5-small-squad-qg

This model is a fine - tuned version of t5-small for the question generation task on the lmqg/qg_squad (dataset_name: default) via lmqg. It aims to generate high - quality questions from given text, which is useful in various natural language processing applications.

🚀 Quick Start

Overview

Usage

💻 Usage Examples

Basic Usage

With lmqg

from lmqg import TransformersQG

# initialize model
model = TransformersQG(language="en", model="lmqg/t5-small-squad-qg")

# model prediction
questions = model.generate_q(list_context="William Turner was an English painter who specialised in watercolour landscapes", list_answer="William Turner")

With transformers

from transformers import pipeline

pipe = pipeline("text2text-generation", "lmqg/t5-small-squad-qg")
output = pipe("generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.")

📚 Documentation

Metrics

The following metrics are used to evaluate the model's performance:

• bleu4
• meteor
• rouge-l
• bertscore
• moverscore

Widget Examples

• Question Generation Example 1:
  • text: "generate question: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records."
• Question Generation Example 2:
  • text: "generate question: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records."
• Question Generation Example 3:
  • text: "generate question: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records ."

Model Index

The model lmqg/t5-small-squad-qg has been evaluated on multiple datasets with different tasks and metrics. Here are some of the key results:

On lmqg/qg_squad (default)

On other datasets (lmqg/qg_squadshifts, lmqg/qg_subjqa with different subsets)

The model has also been evaluated on various subsets of lmqg/qg_squadshifts (e.g., amazon, new_wiki, nyt, reddit) and lmqg/qg_subjqa (e.g., books, electronics, grocery, movies, restaurants, tripadvisor). The detailed metric values for each dataset and subset are provided in the original model card.

📄 License

This model is released under the cc - by - 4.0 license.