A Hierarchical Multi-task Approach for Learning Embeddings from Semantic Tasks

14 Nov 2018 Victor Sanh Thomas Wolf Sebastian Ruder

Much effort has been devoted to evaluate whether multi-task learning can be leveraged to learn rich representations that can be used in various Natural Language Processing (NLP) down-stream applications. However, there is still a lack of understanding of the settings in which multi-task learning has a significant effect... (read more)

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Datasets


Results from the Paper


 Ranked #1 on Relation Extraction on ACE 2005 (Sentence Encoder metric, using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
RESULT BENCHMARK
Relation Extraction ACE 2005 Hierarchical Multi-task RE Micro F1 62.7 # 5
NER Micro F1 87.5 # 4
Sentence Encoder ELMo # 1

Methods used in the Paper


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