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Starter code for robustqa track

  • Download datasets from here
  • Setup environment with conda env create -f environment.yml
  • Train a baseline MTL system with python train.py --do-train --eval-every 2000 --run-name baseline
  • Evaluate the system on test set with python train.py --do-eval --sub-file mtl_submission.csv --save-dir save/baseline-01
  • Upload the csv file in save/baseline-01 to the test leaderboard. For the validation leaderboard, run python train.py --do-eval --sub-file mtl_submission_val.csv --save-dir save/baseline-01 --eval-dir datasets/oodomain_val

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  • Python 98.2%
  • Shell 1.8%