deepmancer/roberta-adapter-fine-tuning
Fine-tuning a RoBERTa model for sentiment analysis on the IMDB movie reviews dataset using the Adapter method and PyTorch Transformers
This project helps data scientists efficiently fine-tune large language models for specific tasks. It takes raw text data, like movie reviews, and outputs sentiment classifications (positive or negative) without needing to retrain the entire model. Anyone working on natural language processing tasks who needs to adapt powerful models to new datasets can use this.
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Use this if you need to perform sentiment analysis or other text classification on your own datasets using powerful pre-trained models, but want to minimize computational resources and training time.
Not ideal if you need to build a sentiment analysis model from scratch without leveraging existing large language models or if your dataset is extremely small.
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Feb 07, 2025
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