5. Glossary
Annotation; Labeling
Annotated data is needed to guide supervised learning. Annotations can relate to a text, a sentence, or even isolated words; they can be linguistic in nature (morphological, syntactic, semantic), or represent the output of a processing task (e.g. the polarity of a text, or the semantic equivalence between two sentences).
Refining; Finetuning
A model trained for a particular task (e.g. one on a language model task) can be transferred to another task by extending the training with other types of data or annotations: this is the refinement stage. In this way, the parameters of a model like BERT can be specialized using a few examples from a sentiment analysis task. Model refinement is one method of transfer learning.
Transfer Learning
Transfer learning...
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Bibliography
- (1) - AHARONI (R.), JOHNSON (M.), FIRAT (O.) - Massively multilingual neural machine translation. - Proceedings of the 2019 conference of the north American chapter of the association for computational linguistics : Human language technologies, volume 1 (long and short papers), Association for Computational Linguistics, p. 3874-3884 (2019)....
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