Next sentence prediction (NSP) is one-half of the training process behind the BERT model (the other being masked-language modeling - MLM).
Where MLM teaches BERT to understand relationships between words - NSP teaches BERT to understand relationships between sentences.
In the original BERT paper, it was found that without NSP, BERT performed worse on every single metric - so it’s important.
Now, when we use a pre-trained BERT model, training with NSP and MLM has already been done, so why do we need to know about it?
Well, we can actually further pre-train these pre-trained BERT models so that they better understand the language used in our specific use-cases. To do that, we can use both MLM and NSP.
So, in this video, we’ll go into depth on what NSP is, how it works, and how we can implement it in code.
Training with NSP:
🤖 70% Discount on the NLP With Transformers in Python course:
2 views
551
210
5 years ago 00:34:20 14
Training BERT Language Model From Scratch On TPUs
2 years ago 00:13:43 2
Training BERT #3 - Next Sentence Prediction (NSP)
4 years ago 00:18:05 7
BERT & NLP Explained
4 years ago 00:02:03 499
Gilbert Burns Powerful Training Highlights | Training World
5 years ago 01:16:06 8
Training Sentiment Model Using BERT and Serving it with Flask API
5 years ago 01:01:15 11
BERT on Steroids: Fine-tuning BERT for a dataset using PyTorch and Google Cloud TPUs
4 years ago 00:13:52 120
The Machine - Bert Kreischer: THE MACHINE
5 years ago 00:11:50 12
BERT Can See Out of the Box
4 years ago 00:27:30 1
DJ Q-Bert Scratch Training . IG LIVE
4 years ago 00:51:48 9
BERT classifier fine-tuning with PyTorch, HuggingFace, and Catalyst. Part 4. Training with Catalyst
4 years ago 00:54:29 16
Stanford CS224N: NLP with Deep Learning | Winter 2020 | BERT and Other Pre-trained Language Models
5 years ago 00:17:49 4
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding | NAACL BEST PAPERS