SlowGuess/NAACL_2022_OCR huggingface dataset:
Regarding the number  $l$  of examples generated through  $\mathcal{M}$ , we can observe that generating a higher number of examples seems to be beneficial in almost every case, especially when dealing with a small dataset. For example, when  $q = 10$  or  $q = 50$ , our DA approach provides the best performance with  $l = 7$  or  $l = 10$ . More generally, we can observe a positive trend in generating at least  $l = 5$  examples with the generation model.
Table 3: A qualitative analysis of the diversity in the Sentiment Analysis task involving SST-5.