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---
language:
- en
tags:
- question-answering
license: apache-2.0
datasets:
- adversarial_qa
- mbartolo/synQA
- squad
metrics:
- exact_match
- f1
model-index:
- name: mbartolo/roberta-large-synqa
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad
type: squad
config: plain_text
split: validation
metrics:
- name: Exact Match
type: exact_match
value: 89.6529
verified: true
- name: F1
type: f1
value: 94.8172
verified: true
- task:
type: question-answering
name: Question Answering
dataset:
name: adversarial_qa
type: adversarial_qa
config: adversarialQA
split: validation
metrics:
- name: Exact Match
type: exact_match
value: 55.3333
verified: true
- name: F1
type: f1
value: 66.7464
verified: true
---
# Model Overview
This is a RoBERTa-Large QA Model trained from https://huggingface.co/roberta-large in two stages. First, it is trained on synthetic adversarial data generated using a BART-Large question generator on Wikipedia passages from SQuAD, and then it is trained on SQuAD and AdversarialQA (https://arxiv.org/abs/2002.00293) in a second stage of fine-tuning.
# Data
Training data: SQuAD + AdversarialQA
Evaluation data: SQuAD + AdversarialQA
# Training Process
Approx. 1 training epoch on the synthetic data and 2 training epochs on the manually-curated data.
# Additional Information
Please refer to https://arxiv.org/abs/2104.08678 for full details. |