Domain Adaptation - SentenceTransformers SBERT : Goal is to adapt text embedding models to your specific text domain. Easy Theory and python code in Jupyter NB / COLAB. Python. SBERT. BERT. Transformers. HuggingFace. Discover how text embeddings model can be adapted to your specific domain. As requested by my viewers (poll in community tab 2 days ago). 00:00 Neural Search 03:09 Domain Adaptation 06:52 Adaptive Pre-training 10:26 Python code in Jupyter NB 15:20 Outlook Improvements #nlproc #SentenceTransformers #python #pythonprogramming #pytorch #colab #ai #deeplearning #machinelearningwithpython #sbert #bert #domain #adaptation All Credits to: https://sbert.net/ @inproceedings{reimers-2019-sentence-bert, title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", author = "Reimers, Nils and Gurevych, Iryna", booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing", month = "11", year = "2019", publisher = "Association for Computational Linguistics", url = "http://arxiv.org/abs/1908.10084", } @inproceedings{wang-2021-TSDAE, title = "TSDAE: Using Transformer-based Sequential Denoising Auto-Encoderfor Unsupervised Sentence Embedding Learning", author = "Wang, Kexin and Reimers, Nils and Gurevych, Iryna", booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021", month = nov, year = "2021", address = "Punta Cana, Dominican Republic", publisher = "Association for Computational Linguistics", pages = "671--688", url = "https://arxiv.org/abs/2104.06979", }