Using an Autoencoder to encode features for k-Means Clustering on the AG News Dataset

The objective of this task is to build a text classification model using the Hugging Face library to classify a dataset of text into one of multiple categories.

This project fine-tunes the DistilBERT model on the AG News dataset for text classification

A text classification project combining attention mechanisms with recurrent models (LSTM and GRU) on the AG News dataset using TensorFlow.

This repository contains the code, model configurations, and report for fine-tuning a roberta-base model using Low-Rank Adaptation (LoRA)- a Parameter-Efficient Fine-Tuning (PEFT) method - on the AG News classification task. The goal was to achieve high test accuracy while keeping trainable parameters under 1 million.

Predicting the topic of news articles