1 Introduction
Table 5: The weighted F1-scores obtained by the identifier using LM adaptation with different values of k when tested on the development partition of the GDI 2017 dataset.
['[ITALIC]  [BOLD] k 1 or 2', '[BOLD] weighted F1-score 0.890', '[ITALIC]  [BOLD] k 30, 35, or 40', '[BOLD] weighted F1-score 0.899']
5.2.2 Experiments with language model adaptation First, we determined the best value for the number of splits k using the development partition. with different values of k on the development partition using the same parameters with the HeLI 2.0 method as for the baseline. The results with k=1 are always equal to the baseline. If k is very high the identification becomes computationally costly as the number of identifications grows exponentially in proportion to k. The absolute increase of the F1-score on the development partition was 0.01 when using k=45.