Smaller Text Classifiers with Discriminative Cluster Embeddings
Table 2: Test results. Model sizes are in MB.
['size', 'AG News 0.05', 'AG News 0.1', 'DBPedia 0.05', 'DBPedia 0.1', 'Yelp Full 0.05', 'Yelp Full 0.1', 'Yelp Polarity 0.05', 'Yelp Polarity 0.1']
The test results are reported based on model performance on the development set for different model sizes. The models are consistent between development and test, as our cluster models with max size 0.05MB outperform SE across datasets, with ME having the highest accuracies.