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🎁 Free NLP for Semantic Search Course: https://www.pinecone.io/learn/nlp BERT has enjoyed unparalleled success in NLP thanks to two unique training approaches, masked-language modeling (MLM), and next sentence prediction (NSP). In many cases, we might be able to take the pre-trained BERT model out-of-the-box and apply it successfully to our own language tasks. But often, we might need to pre-train the model for a specific use case even further. Further training with MLM allows us to tune BERT to better understand the particular use of language in a more specific domain. Out-of-the-box BERT - great for general purpose use. Fine-tuned with MLM BERT - great for domain-specific use. In this video, we'll cover exactly how to fine-tune BERT models using MLM in PyTorch. 👾 Code: https://github.com/jamescalam/transfo... Meditations data: https://github.com/jamescalam/transfo... Understanding MLM: • Training BERT #1 - Masked-Language Modelin... 🤖 70% Discount on the NLP With Transformers in Python course: https://bit.ly/3DFvvY5 📙 Medium article: https://towardsdatascience.com/masked... 🎉 Sign-up For New Articles Every Week on Medium! / membership 📖 If membership is too expensive - here's a free link: https://towardsdatascience.com/masked... 🕹️ Free AI-Powered Code Refactoring with Sourcery: https://sourcery.ai/?utm_source=YouTu...