Topic: fine-tuning-bert Goto Github
Some thing interesting about fine-tuning-bert
Some thing interesting about fine-tuning-bert
fine-tuning-bert,Turkish Hate Speech Detection
User: alpcansoydas
fine-tuning-bert,WSD for Word-in-Context (WiC) disambiguation, experimenting with BERT feature-based and fine-tuning approaches (GlossBERT)
User: andrea-gasparini
Home Page: https://github.com/sapienzanlp/nlp2021-hw3
fine-tuning-bert,❓Fine-tuning BERT for extractive QA on SQuAD 2.0
User: angelosps
fine-tuning-bert,External Knowledge Infusion using INCIDecoder into BERT for Chemical Mapping
User: anshumaan-chauhan02
fine-tuning-bert,Health Progress Prediction and Goal Attainment Analysis in Patient Discharge Summaries with BERT and Tensorflow. - Feb 2022 - Jun 2023
User: bilalhameed248
fine-tuning-bert,Question Answering with a Fine-Tuned BERT
User: cag9
fine-tuning-bert,Estudio del carácter patogénico de variantes humanas mediante deep learning. Fine-tuning de BERT para la representación de enfermedades: un método de aprendizaje sobre datasets de textos biomédicos.
User: dgomndez
fine-tuning-bert,
User: jedirhymetrix
fine-tuning-bert,A PyTorch Lightning Implementation of Multi-Language Identification using a SentenceTransformer model pre-trained on English. Work done while interning at ByteFuse.
User: kayodeolaleye
fine-tuning-bert,Using BERT models to perform sentiment analysis on women's clothing
User: ongaunjie1
Home Page: https://huggingface.co/ongaunjie/distilbert-cloths-sentiment
fine-tuning-bert,
User: r-sajal
fine-tuning-bert,It's Smart-Question Answering System on short as well as long documents. It can automatically find answers to matching questions directly from documents. The deep learning language model converts the questions and documents to semantic vectors to find the matching answer.
User: satyamsoni23
fine-tuning-bert,Successfully developed a fine-tuned BERT transformer model which can effectively perform emotion classification on any given piece of texts to identify a suitable human emotion based on semantic meaning of the text.
User: sayamalt
fine-tuning-bert,Successfully established a Seq2Seq with attention model which can perform English to Spanish language translation up to an accuracy of almost 97%.
User: sayamalt
fine-tuning-bert,Successfully developed a news category classification model using fine-tuned BERT which can accurately classify any news text into its respective category i.e. Politics, Business, Technology and Entertainment.
User: sayamalt
fine-tuning-bert,Successfully developed a resume classification model which can accurately classify the resume of any person into its corresponding job with a tremendously high accuracy of more than 99%.
User: sayamalt
fine-tuning-bert,Notebooks for fine-tuning and evaluating a pre-trained BERT model to the task of semantic parameter matching in Web APIs
User: sebastiankotstein
fine-tuning-bert,Notebooks for fine-tuning and evaluating pre-trained BERT models to tasks for semantic search in Web API documentation
User: sebastiankotstein
fine-tuning-bert,Initially implement Document-Retrieval-System with SBERT embeddings and evaluate it in CORD-19 dataset. Afterwards, fine tune BERT model with SQuAD.v2 dataset so as to evaluate it in Question Answering task.
User: spyros-briakos
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