Downstream tasks fine-tuning using BERT
Transfer Fine Tuning: A BERT Case Study
... into BERT in order to generate suitable representations for seman- tic equivalence assessment instead of increas- ing the model ...understanding tasks confirm that our method effectively improves a smaller ...
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ArabGlossBERT: Fine-Tuning BERT on Context-Gloss Pairs for WSD
... and “a number of pages bound together”. WSD has been a challenging task for many years but has gained recent attention due to the advances in contextualized word embedding models such as BERT (Devlin et al., ...
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Effects of inserting domain vocabulary and fine tuning BERT for German legal language
... not using action buttons placed on the top and on the result pre- ...represented using background color (light green for relevant and light red for unrelevant) and it’s linked to the preview thumbnail on ...
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Cross Lingual Lemmatization and Morphology Tagging with Two Stage Multilingual BERT Fine Tuning
... multilingual BERT model and apply several fine-tuning strategies introduced by UDify demonstrating exceptional evaluation perfor- mance on morpho-syntactic ...that fine-tuning ...
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BLCU NLP at COIN Shared Task1: Stagewise Fine tuning BERT for Commonsense Inference in Everyday Narrations
... swer separately and then employs attention mech- anism to model interactions among them. This kind of method performs well on questions that can be answered from given passage texts but shows limited performance on ...
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Cardiff University at SemEval-2020 Task 6: fine-tuning BERT for domain-specific definition classification
... Early attempts to solve this task relied on rule-based methods (Klavans and Muresan, 2001; Cui et al., 2005). However, such methods are typically only able to detect explicit, direct and structured definitions, which ...
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AIG Investments AI at the FinSBD Task: Sentence Boundary Detection through Sequence Labelling and BERT Fine tuning
... embeddings. BERT is trained using two unsuper- vised prediction tasks, Masked Language Model and Next Sentence ...To fine-tune BERT towards a sequence labelling task, the final hidden ...
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On Commonsense Cues in BERT for Solving Commonsense Tasks
... and BERT Layer We further investigate two specific questions on the commonsense knowledge ...does BERT rely on the most for making its deci- ...that BERT uses come more from pre-training or ...First, ...
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New Benchmark Corpus and Models for Fine-grained Event Classification: To BERT or not to BERT?
... of tasks and challenges on automated event extraction, including event classifi- cation, has been organised over the years, relatively little work has been reported on approaches for fine-grained event ...
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Fine tune BERT with Sparse Self Attention Mechanism
... of tasks. However, the current fine-tuning models usually employ the pre- trained BERT as initialization of the networks and do not pay enough attention on how to dynami- cally control this ...
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Assessing the impact of OCR quality on downstream NLP tasks
... to fine-tune an existing pre-trained model, Word2Vec LM (Mikolov et ...2013) using the Gensim ...pre-trained using ≈ ...new fine-tuned LMs using human-corrected and OCR’d ...words ...
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Fine-Tuning Bidirectional Encoder Representations From Transformers (BERT)-Based Models on Large-Scale Electronic Health Record Notes: An Empirical Study
... dictionaries provided by DNorm. We employed gold mentions as input in order to compare with DNorm. Besides precision, recall, and F1, we also analyzed statistical significances between different models. First, the ...
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Sentence BERT: Sentence Embeddings using Siamese BERT Networks
... other tasks. Here, we think fine-tuning BERT as de- scribed by Devlin et ...new tasks is the more suitable method, as it updates all layers of the BERT ...
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IMHO Fine Tuning Improves Claim Detection
... challenging assumptions that conceptualizations across AM data sets are divergent and that MTL is difficult for semantic or higher-level tasks. Rosenthal and McKeown (2012) were among the first to conduct ...
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miR-210: fine-tuning the hypoxic response
... by using anti- miR-210 accelerates cell cycle progression, whereas overexpression of miR-210 leads to cell cycle arrest in the G 1 /G 0 and G 2 /M phases (Tsuchiya et ...responders downstream of the genes ...
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Evaluation of Stacked Embeddings for Bulgarian on the Downstream Tasks POS and NERC
... behind BERT and the reason to propose it is to improve the fine-tuning based approaches, thus in the future experiments with Bulgarian NERC the idea should be ...tested. Fine-tuning is ...
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BertAA: BERT fine-tuning for Authorship Attribution
... Architecture 03 Dense Layer Pre-trained BERT Ber t F ine-tuning Logistic Regression Stylistic features Logistic Regression Hybrid features Training data BertAA + Style + Hybrid?. Cl[r] ...
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Fine Grained Propaganda Detection with Fine Tuned BERT
... 4 Conclusion and Future Work This paper describe our winning solution in the Fragment Level Classification (FLC) task of the Fine-Grained Propaganda Detection Challenge in NLP4IF’19. Our approach is based on the ...
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The fine-tuning argument
... the fine-tuning in the world as well as the existence of our earth with its relatively favorable conditions (Ward & Brownlee, 2000), evolution has been walking a tightrope so as to produce as much as ...
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Data Fine-Tuning
... a few pixels of an image are modified to fool the classifier. (Carlini and Wagner 2017) introduced three adversarial at- tacks and showed the failure of defensive distillation (Carlini and Wagner 2016) for targeted ...
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