1. Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models
- Author
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Merrick, Luke, Xu, Danmei, Nuti, Gaurav, and Campos, Daniel
- Subjects
Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Information Retrieval - Abstract
This report describes the training dataset creation and recipe behind the family of \texttt{arctic-embed} text embedding models (a set of five models ranging from 22 to 334 million parameters with weights open-sourced under an Apache-2 license). At the time of their release, each model achieved state-of-the-art retrieval accuracy for models of their size on the MTEB Retrieval leaderboard, with the largest model, arctic-embed-l outperforming closed source embedding models such as Cohere's embed-v3 and Open AI's text-embed-3-large. In addition to the details of our training recipe, we have provided several informative ablation studies, which we believe are the cause of our model performance., Comment: 17 pages, 11 Figures, 9 tables
- Published
- 2024