Archives for bert - Page 4
When Transformers Fail
Transformers are the de facto architecture of choice for natural language processing tasks. Since their introduction three years ago, Transformers have undergone several modifications. Recently, a team of researchers from Google Research found that most modifications do not meaningfully improve transformers’ performance. Some of the popular modifications to Transformers include various activation functions (such as…
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XLnet is an extension of the Transformer-XL model. It learns bidirectional contexts using an autoregressive method. Let’s first understand the shortcomings of the BERT model so that we can better understand the XLNet Architecture. Let’s see how BERT learns from data.
The post Guide to XLNet for Language Understanding appeared first on Analytics India Magazine.
XLnet is an extension of the Transformer-XL model. It learns bidirectional contexts using an autoregressive method. Let’s first understand the shortcomings of the BERT model so that we can better understand the XLNet Architecture. Let’s see how BERT learns from data.
The post Guide to XLNet for Language Understanding appeared first on Analytics India Magazine.
Recently, researchers from Facebook AI introduced a Transformer architecture, that is known to be with more memory as well as time-efficient, called Linformer. According to the researchers, Linformer is the first theoretically proven linear-time Transformer architecture. For a few years now, the number of parameters in Natural Language Processing (NLP) transformers has grown drastically, from…
The post Meet Linformer: The First Ever Linear-Time Transformer Architecture By Facebook appeared first on Analytics India Magazine.
“Over 20 million active patents and applications exist worldwide with each patent containing an average of ~10,000 words.” What’s one thing that is common amongst many billion-dollar or even trillion-dollar companies like Google or Amazon? It is their unique, patented idea. Be it Google’s PageRank algorithm or Amazon’s 1-click option; they were first presented as…
The post How Google Might Help You Find The Next Billion Dollar Idea appeared first on Analytics India Magazine.
“Over 20 million active patents and applications exist worldwide with each patent containing an average of ~10,000 words.” What’s one thing that is common amongst many billion-dollar or even trillion-dollar companies like Google or Amazon? It is their unique, patented idea. Be it Google’s PageRank algorithm or Amazon’s 1-click option; they were first presented as…
The post How Google Might Help You Find The Next Billion Dollar Idea appeared first on Analytics India Magazine.
Recently, the researchers at Amazon introduced an optimal subset of the popular BERT architecture for neural architecture search. This smaller version of BERT is known as BORT and is able to be pre-trained in 288 GPU hours, which is 1.2% of the time required to pre-train the highest-performing BERT parametric architectural variant, RoBERTa-large. Since its…
The post This New BERT Is Way Faster & Smaller Than The Original appeared first on Analytics India Magazine.
GPT-3 Vs BERT For NLP Tasks
The immense advancements in natural language processing have given rise to innovative model architecture like GPT-3 and BERT. Such pre-trained models have democratised machine learning, which allows even people with less tech background to get their hands-on building ML applications, without training a model from scratch. With capabilities of solving versatile problems like making accurate…
The post GPT-3 Vs BERT For NLP Tasks appeared first on Analytics India Magazine.
This article is a demonstration of how simple and powerful transfer learning models are in the field of NLP. We will implement a text summarizer using BERT that can summarize large posts like blogs and news articles using just a few lines of code.
The post Hands-on Guide To Extractive Text Summarization With BERTSum appeared first on Analytics India Magazine.
NLP Models have shown tremendous advancements in syntactic, semantic and linguistic knowledge for downstream tasks. However, that raises an interesting research question — is it possible for them to go beyond pattern recognition and apply common sense for word-sense disambiguation? Thus, to identify if BERT, a large pre-trained NLP model developed by Google, can solve…
The post Is Common Sense Common In NLP Models? appeared first on Analytics India Magazine.