Unifying Question Answering, Text Classification, and Regression via Span Extraction
Table 4: Development set accuracy scores on three of the GLUE tasks when fine-tuned only on a constrained subset of examples. Bold indicates best score for a task.
['[EMPTY]', 'SST', 'MRPC', 'RTE']
For this experiment, we follow Phang et al. The rest of the experimental setup remains unchanged. When used in conjunction with STILTs, the performance improves as expected and, in a majority of cases, significantly exceeds that of the corresponding baseline that does not use span-extraction.