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xlm-r-base-uit-viquad
chieunq/xlm-r-base-uit-viquad
xlm-r-base-uit-viquad is a question answering model from chieunq. Use it when the input is a question plus a passage. It is set up for transformers.
We fined-tune model XLM-Roberta-base in UIT-vquad dataset (https://arxiv.org/pdf/2009.14725.pdf) and argument data technique - EM (exact match) : 65.63 - F1 : 85.63
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At a glance
- Task
- Question Answering
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Dec 4, 2022
- Updated
- Dec 13, 2022
- SHA
- 5dd7c218
Try a prompt
Datasets
Model card
From the Hugging Face model README
We fined-tune model XLM-Roberta-base in UIT-vquad dataset (https://arxiv.org/pdf/2009.14725.pdf) and argument data technique
Performance
- EM (exact match) : 65.63
- F1 : 85.63
How to run
from transformers import pipeline
# Replace this with your own checkpoint
model_checkpoint = "chieunq/xlm-r-base-uit-viquad"
question_answerer = pipeline("question-answering", model=model_checkpoint)
context = """
Nhóm của chúng tôi là sinh viên năm 4 trường ĐH Công Nghệ - ĐHQG Hà Nội. Nhóm gồm 3 thành viên : Nguyễn Quang Chiều, Nguyễn Quang Huy và Nguyễn Trần Anh Đức . Đây là pha Reader trong dự án cuồi kì môn Các vấn đề hiện đại trong CNTT của nhóm .
"""
question = "3 thành viên trong nhóm gồm những ai ?"
question_answerer(question=question, context=context)
Output
{'score': 0.9928902387619019,
'start': 98,
'end': 158,
'answer': 'Nguyễn Quang Chiều, Nguyễn Quang Huy và Nguyễn Trần Anh Đức.'}
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2
- Task
- Question Answering
- Library
- transformers
- Type
- xlm-roberta
- Languages
- vi
- Created
- Dec 4, 2022
- Updated
- Dec 13, 2022