Cross-lingual Zero- and Few-shot Hate Speech Detection utilising frozen Transformer Language Models and AXEL
Table 5: Zero-shot performance comparison of XLM base XLM_Dense(G), XLM_Att(G), and XLM1L_AXEL (F) across languages and predictions on the translated test set in F1 in %. This shows that the latter outperforms other XLM based models as well as that the output latent structure for various languages differs. train⇒test; original→translation.
['[EMPTY]', 'Dense', 'Att', 'AXEL']
Overall, the models show general learnability, however, lack generalisability and the performance is much worse than in our monolingual experiments. To probe if the causes of the performance loss are either on the data or the model side, we carried out additional experiments. the test set into the language of the training set.