مرکز سیستم های اطلاعات و علوم داده شریف
Sharif Center For Information Systems and Data Science کانال رسمی مرکز سیستم های اطلاعات و علوم داده دانشگاه شریف سایت: icst.sharif.edu/data/about لینکدین: www.linkedin.com/company/data-icst-sharif/ راه ارتباطی: [email protected]
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We’ve obtained state-of-the-art results on a suite of diverse language tasks with a scalable, task-agnostic system, which we’re also releasing. Our approach is a combination of two existing ideas: transformers and unsupervised pre-training. These results provide a convincing example that pairing supervised learning methods with unsupervised pre-training works very well; this is an idea that many have explored in the past, and we hope our result motivates further research into applying this idea on larger and more diverse datasets.
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