Towards Hate Speech Detection at Large via Deep Generative Modeling
Table 2: ROUGE-L scores of data generated by the GPT-2 language model per dataset. These values indicate on low similarity between the generated sequences and the sequences on which the model has been fine-tuned, for each dataset and class.
['Source dataset', 'Generated hate', 'Generated non-hate']
We further wished to verify that the generated sequences depart from the seed labeled examples, forming new and diverse language usage, as opposed to duplicating or repeating parts of the input examples. (nothing in common) to 1 (identical sequences). As shown, the similarity scores are low, indicating that the rich language model encoded within GPT-2 was effectively leveraged for generating new and different text sequences.