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Accelerate hyperparameter grid search for sentiment analysis with BERT models using Weights & Biases, Amazon EKS, and TorchElastic

AWS Machine Learning Blog

Transformer-based language models such as BERT ( Bidirectional Transformers for Language Understanding ) have the ability to capture words or sentences within a bigger context of data, and allow for the classification of the news sentiment given the current state of the world. Solutions Architect in the ML Frameworks Team.

BERT 98
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This AI Paper from Cohere Enhances Language Model Stability with Automated Detection of Under-trained Tokens in LLMs

Marktechpost

Tokenization is essential in computational linguistics, particularly in the training and functionality of large language models (LLMs). The study demonstrated the effectiveness of this new method by applying it to several well-known models, including variations of Google’s BERT and OpenAI’s GPT series.

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Alibaba Researchers Unveil Unicron: An AI System Designed for Efficient Self-Healing in Large-Scale Language Model Training

Marktechpost

The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. The computational intensity required and the potential for various failures during extensive training periods necessitate innovative solutions for efficient management and recovery.

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Building a Sentiment Classification System With BERT Embeddings: Lessons Learned

The MLOps Blog

Sentiment analysis, commonly referred to as opinion mining/sentiment classification, is the technique of identifying and extracting subjective information from source materials using computational linguistics , text analysis , and natural language processing. Words like “Descent”, “Average”, etc. are assigned a negative label.

BERT 52
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ML and NLP Research Highlights of 2021

Sebastian Ruder

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). Pre-trained models were applied in many different domains and started to be considered critical for ML research [1]. 6] such as W2v-BERT [7] as well as more powerful multilingual models such as XLS-R [8]. What happened?  

NLP 52
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The State of Multilingual AI

Sebastian Ruder

Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. Representation of African NLP Researchers in top ML and NLP venues. *: does not consider African authors working abroad.