Papers with fine-tuning one model

1 papers
Multilingual Constituency Parsing with Self-Attention and Pre-Training (P19-1)

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Challenge: a range of pre-training conditions can be used for constituency parsing, but large model sizes make it expensive to train separate models for each language.
Approach: They compare the benefits of no pre-training, fastText, ELMo, and BERT for English . they also find that pre- training is beneficial across all 11 languages tested .
Outcome: The proposed model outperforms fastText, ELMo, and BERT for English . but large model sizes make it expensive to train separate models for each language .

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