Fast Cross-domain Data Augmentation through Neural Sentence Editing
Table 4: Accuracy on the SST-2 dataset
['Training data used', 'Original data', 'N = 1', 'N = 2']
Same as before we performed the experiment using 20, 50 and 100 percent of the data. Here we notice that we get an improvement only when using 20 and 50% of the data. The reason for this could be because using 100% of the original data is enough for the model to be able to generalize properly and by augmenting the data we are just adding samples that are very close to the real data so it does not improve the performance.