metadata

language:
  - en
license: apache-2.0
tags:
  - question-answering
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:
          - type: exact_match
            value: 89.6529
            name: Exact Match
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjM2NTJjZDk0ZWEwM2Q5Njk5NmY5Mzk4ODk4OTViMjZlODlkMTM4M2ZlM2Q0YjgwMWY4OGUzM2QwYTk0YTBhMSIsInZlcnNpb24iOjF9.ZafZxhyJS2xpjYDMhyTO8wVmeZJrwbeJmyvZypMbhUJORR194GJwgttUp150XG3MUFVFqPYQh8tuzpm_QQ6sAA
          - type: f1
            value: 94.8172
            name: F1
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYWE3OGFlYWZmZThhNDMwYzU4OTY3NmU4NmNlYTcwODVkZmQ3N2FlZmE0NGM2Mzk3Nzc2ZmZmNzhkM2NiNzNiMCIsInZlcnNpb24iOjF9.LF4-uxpGMMr7oP_C_SAYHgKMw6I9Sz8FiRnofaD9WFkQZrGPaPR1HjvC6sWo2Nyy5uuD76bowY278Qf8kWwLBw
      - task:
          type: question-answering
          name: Question Answering
        dataset:
          name: adversarial_qa
          type: adversarial_qa
          config: adversarialQA
          split: validation
        metrics:
          - type: exact_match
            value: 55.3333
            name: Exact Match
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmIwZTdmNzg4MmE5YjM2MzkxOWFmM2JmODMzZDhhZGY5YWE0Njc2MmY0YzIyNzEwMGU0MDIwOTZjZTEyZjk5YSIsInZlcnNpb24iOjF9.dNd-MElaXPRrYSgvzxcMyN87ts0iyON4mdQChv68AIspmQKAUKRVzdm7w0mhRyvzG8a7aDl7dgUFCZVxd7-FAQ
          - type: f1
            value: 66.7464
            name: F1
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDU4ZTE0MTliNmJjYmFjZmI4MjEwMWRiMjJmZjhjYzBkY2Q0ZGUzMzZlMTZkNmFlZThmYzMyMThjN2IwMjI3NSIsInZlcnNpb24iOjF9.A4AxMaEXNDRZaR_ZazFH3PUhi-jn0JniWv7xEXGM3oidhR6hsWNi5twqegAAuZe56YDPxCUhuoGahovcWmoaBQ

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.