LLM Safeties Evaluation
The project aimed to refine a language model's abilities in various linguistic tasks such as text classification, sentiment analysis, and question-answering.
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With over three years of experience in data labeling and AI training data preparation, I have developed a robust skill set that includes annotation, data categorization, and quality control, specializing in the fields of natural language processing and computer vision. I have contributed to several significant projects, notably in the development of an AI-driven content moderation tool and a smart OCR system, LLMs chatbot where my precise data labeling directly improved the AI's performance, reliability, and safety.
The project aimed to refine a language model's abilities in various linguistic tasks such as text classification, sentiment analysis, and question-answering.
The LLM Evaluate project was focused on assessing and enhancing the performance of a language model through rigorous data labeling and evaluation tasks.
The scope of the LLM Rewriter project was focused on improving a language model's capability to understand and rephrase text accurately.
The scope of the project encompassed the labeling of over 500,000 pages, each requiring detailed attention to ensure that text was accurately captured and categorized according to document type and content specificity. The specific data labeling tasks I performed included Review Text Annotation, Error Tagging and Quality Verification.
Master of Science in Data Science, Data Science
Bachelor of Arts, Linguistic
Project Manager Assistant
SAP Implementation Project: Key User on MM and PM modules