What do Models Learn from Question Answering Datasets?
Table 4: F1 scores of each fine-tuned model evaluated on each test set
['Evaluated on', 'Evaluated on', 'Evaluated on SQuAD', 'Evaluated on TriviaQA', 'Evaluated on NQ', 'Evaluated on QuAC', 'Evaluated on NewsQA', 'Evaluated on Avg Δ']
We test generalizability by fine-tuning models on each of the datasets and evaluating them against all five test sets without any further fine-tuning. The rows show a single model’s performance across all five datasets, and the columns show the performance of all the models on a single dataset. The model-on-self baseline is indicated in bold. The final column shows the average difference between each model’s performance on a dataset and the model-on-self baseline.