Benchmarking Popular Classification Models’ Robustness to Random and Targeted Corruptions
Table 4: Baseline Accuracies of the FastText and Bi-LSTM models evaluated on the four datasets
['[BOLD] Dataset', '[BOLD] FastText', '[BOLD] Bi-LSTM']
To be consistent across datasets and models, we apply minimal pre-processing to the data. All punctuation - except sentence delimiters - and HTML tags are removed from the documents and the text is then converted to lower case. We do not remove stopwords. We then train the models with this pre-processed data. We use FastText with default hyperparameters of vector size 10, learning rate 0.1 and wordNgrams 2.