To Tune or Not to Tune? Adapting Pretrained Representations to Diverse Tasks
Table 5: Comparison of CoNLL 2003 NER development set performance (F1) for ELMo for both feature extraction and fine-tuning. All results averaged over five random seeds.
['[BOLD] Model configuration', '[BOLD] F1']
We evaluate whether adding parameters is useful for both adaptation settings on NER. We find that additional parameters are key for , but hurt performance with .