Hi, I’m Annie! →

I’m a narrative-driven designer with a love for prototyping, storytelling, and visual craft. 
 
Selected Projects:Blooming Orchids
Fluidnotes
Parsons MSDV
Breathscape Kit
Airy
P5.Party Games




Sake AI
Analyzing Sake Branding using BART Transformer and LoRA-based Training
TEAMAnnie Lee
Ani Matevosian
Yuta Itagaki
DURATION 2 Days Sprint (Feb 2025)
TOOLSStable Diffusion XL (SDXL), DreamBooth, LoRA, Hugging Face Transformers (BART), PythonSKILLSGenerative AI Training, Fine Tuning Diffusion Models, Transformer-based NLP Training, Dataset Curation, Prompt Engineering
PROJECT OVERVIEW
SAKE.ai analyzes sake branding using BART transformer and LoRA-based training to identify trends, generate labels, and provide food pairing recommendations based on the flavors, aromas, and recommended temperature of each sake. With practical exploration of Transformers, this project focuses on attention-based architecture for data visualization.


THE CHALLENGE
We noticed a missing element in typical sake labels—how much can we infer about flavors, aromas, and ideal drinking temperature just from the design?

Are there patterns or emerging trends in sake branding?








LABEL GENERATION MODEL
Fine-tune Stable Diffusion XL (SDXL) with DreamBooth using LoRA (Low-Rank Adaptation) for local usage.

The model is trained with 3O images and adjusting prompts manually with temperature, flavor, and aroma data.




LABEL GENERATION MODEL OUTPUT





PAIRING RECOMMENDATION MODEL
Using BART, a transformer model from Hugging Face, this system predicts food pairings based on sake descriptions by learning next-sentence relationships from a curated dataset. The dataset includes flavor-food pairings we collected from the Sakenomy website and data generated from ChatGPT.





SAKE.AI IN ACTION
Input → 
Floral Sake with Sweet Characteristics, Best served at room temperature


BART Output:
Light tempura, fresh sashimi, vegetable dishes

SDXL Output:




Next Steps
→  Web scrape Sakenomy for more data to generate more diverse food pairings.
→ Build a label generation tool that visualizes the flavors and drinking recommendations like temperature and food pairings.