Parameter-Efficient Fine-Tuning of the Google Gemma-7B Model for Hausa Language Sentiment Analysis Task Using Low-Rank Adaptation Technique

Efficient fine Tuning of Whisper for Algerian Dialect Automatic Speech Recognition using Low Rank Adaptation

Gradient-Based Importance Smoothing for Dynamic Rank Allocation in Parameter-Efficient Fine-Tuning for Low-Resource Languages

Abstract Large pre-trained language models (PLMs) achieve state-of-the-art perform

Two-Stage Bengali Sentiment Classification: Domain Adaptation Through Continual Learning and Parameter-Efficient Fine-Tuning

Understanding sentiment in low-resource languages remains a key challenge for Natural Language Proce

IncreLoRA: Incremental Parameter Allocation Method for Parameter-Efficient Fine-tuning

With the increasing size of pre-trained language models (PLMs), fine-tuning all the parameters in th

bagwai/fine-tuned-gemma-7b-Hausa

Investigating the Impact of Language-Adaptive Fine-Tuning on Sentiment Analysis in Hausa Language Using AfriBERTa

Sentiment analysis (SA) plays a vital role in Natural Language Processing (NLP) by ~identifying sent