Master fine-tuning Transformers, comparing deep learning architectures, and deploying sentiment analysis models
15 hours ago
This project provides a detailed, step-by-step guide to fine-tuning a Transformer model for sentiment classification while taking you through the entire Machine Learning pipeline.
Curious for more? The COMPLETE project repository awaits you in the Bibliography section at the end of this tutorial, where you can explore every detail hands-on.
We begin by defining the problem and preparing data, then progress through building, training, and evaluating models.
The focus is on fine-tuning a Transformer model, but we also compare its performance with two traditional deep learning architectures, ensuring a well-rounded understanding of the methodologies involved.
Key concepts like deep learning architecture, metric interpretation, and deployment are highlighted throughout the project.
This is a comprehensive learning experience, designed to deepen your understanding of modern Machine Learning techniques.
The dataset used was sourced from carblacac/twitter-sentiment-analysis (Apache 2.0…