Master tuning Transformers, comparing deep learning architectures, and implementing sentiment analysis models.
This project provides a detailed description, Step-by-step guide to fine-tuning a Transformer model for sentiment classification while taking you through the entire machine learning process.
Curious for more? He COMPLETE project repository awaits you in the Bibliography section at the end of this tutorial, where you can explore every detail hands to work.
We start by defining the problem and preparing data, then move through building, training, and evaluating models.
The focus is on tune a transformer modelbut we also compare its performance with two traditional deep learning architecturesensuring a complete understanding of the methodologies involved.
Key concepts such as deep learning architecture, metric interpretation, and implementation are highlighted throughout the project.
This is a comprehensive learning experiencedesigned to deepen your understanding of modern machine learning techniques.
The data set used came from <a target="_blank" class="af ob" href="https://huggingface.co/datasets/carblacac/twitter-sentiment-analysis” rel=”noopener ugc nofollow” target=”_blank”>carblacac/twitter-sentiment-analysis (Apache 2.0…
