Fine-Tuning Pretrained Language Models:Weight Initializations, Data Orders, and Early Stopping
Table 4: p-values from ANOVA indicate that there is evidence to reject the null hypothesis that the performance of the best and worst WIs and DOs have distributions with the same means (p<0.05).
['[EMPTY]', 'MRPC', 'RTE', 'CoLA', 'SST']
For all datasets, we find the best and worst DOs and WIs are significantly different in their expected performance (p<0.05). We include a discussion of the assumptions behind ANOVA in the appendix.