Evaluate question answering with squad dataset

aycha · October 7, 2021, 9:33am

Hello everybody

I want to build question answering system by fine tuning bert using squad1.1 or squad2.0
i would like to ask about evaluating question answering system, i know there is squad and squad_v2 metrics, how can we use them when fine-tune bert with pytorch?
thank you

nbroad · October 7, 2021, 5:26pm

This example should hopefully answer your question.

github.com

huggingface/transformers/blob/master/examples/pytorch/question-answering/run_qa.py

#!/usr/bin/env python
# coding=utf-8
# Copyright 2020 The HuggingFace Team All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Fine-tuning the library models for question answering.
"""
# You can also adapt this script on your own question answering task. Pointers for this are left as comments.

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If the purpose is to have a good question answering model, you could also use one of the many pretrained models on the hugging face model hub. Models - Hugging Face

aycha · October 10, 2021, 7:29am

thanks for your response

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Evaluate question answering with squad dataset

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