Romy Chandra Wijaya

Key Skills

Software

Appen

CVAT

Data Annotation Tech

Datumbox

Datasaur

Datature

Dataturk

Deep Systems

Figure Eight

Google Cloud Vertex AI

Label Studio

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Computer Code Programming

Document

Top Task Types

Action Recognition

Classification

Entity Ner Classification

Evaluation Rating

Polygon

Freelancer Overview

I have experience in data labeling and AI training projects, particularly in the field of natural language processing (NLP). My expertise includes text annotation, content classification, entity extraction, sentiment analysis, and language model response evaluation and curation. I am accustomed to working with strict labeling guidelines and maintaining consistent data quality, both for Indonesian and English. Furthermore, I have a background in professional writing and editing, which strengthens my ability to assess the accuracy and appropriateness of text across various contexts. My experience in LLM (Large Language Model)-based projects enables me to effectively contribute to improving model performance through quality-based feedback and robust linguistic context.

Labeling Experience

Text Labeling and Language Model Evaluation for Multilingual NLP Projects

AppenTextEntity Ner ClassificationClassification

In this project, I was responsible for labeling and evaluating text for training and fine-tuning large language models (LLMs) in Indonesian and English. Key tasks included sentence classification based on tone and intent, named entity annotation (NER), evaluating model responses to prompts, and writing and refining prompt-responses in the context of questions and answers and text summaries. I was also involved in content translation and localization, as well as stylistic adjustments for varying levels of formality. The project involved thousands of data units, with high-quality standards such as Cohen's Kappa for consistency and multiple review.

In this project, I was responsible for labeling and evaluating text for training and fine-tuning large language models (LLMs) in Indonesian and English. Key tasks included sentence classification based on tone and intent, named entity annotation (NER), evaluating model responses to prompts, and writing and refining prompt-responses in the context of questions and answers and text summaries. I was also involved in content translation and localization, as well as stylistic adjustments for varying levels of formality. The project involved thousands of data units, with high-quality standards such as Cohen's Kappa for consistency and multiple review.

2020

Education

Work History