Model: vocabtrimmer/mt5-small-trimmed-es-30000-esquad-qg
Author: vocabtrimmer
Pipeline: text-generation
Library: transformers
Tags: transformers, pytorch, mt5, text2text-generation, question generation, es, dataset:lmqg/qg_esquad, arxiv:2210.03992, license:cc-by-4.0, model-index, endpoints_compatible, region:us
Card metadata: license: cc-by-4.0
metrics: bleu4, meteor, rouge-l, bertscore, moverscore
language: es
datasets: lmqg/qg_esquad
pipeline_tag: text2text-generation
tags: question generation
widget: text: del <hl> Ministerio de Desarrollo Urbano <hl> , Gobierno de la India.
example_title: Question Generation Example 1, text: a <hl> noviembre <hl> , que es también la estación lluviosa.
example_title: Question Generation Example 2, text: como <hl> el gobierno de Abbott <hl> que asumió el cargo el 18 de septiembre de 2013.
example_title: Question Generation Example 3
model-index: name: vocabtrimmer/mt5-small-trimmed-es-30000-esquad-qg
results: task: name: Text2text Generation
type: text2text-generation
dataset: name: lmqg/qg_esquad
type: default
args: default
metrics: name: BLEU4 (Question Generation)
type: bleu4_question_generation
value: 9.66
verified: no, name: ROUGE-L (Question Generation)
type: rouge_l_question_generation
value: 24.04
verified: no, name: METEOR (Question Generation)
type: meteor_question_generation
value: 22
verified: no, name: BERTScore (Question Generation)
type: bertscore_question_generation
value: 84.29
verified: no, name: MoverScore (Question Generation)
type: moverscore_question_generation
value: 58.96
verified: no
Likes: 0 | All-time downloads: 277
Created: 2023-03-16 17:51:37