Using the Hugging Face Trainer I use the RoBERTa model to compete in the Microsoft Research Sentence Completion Challenge to achieve an accuracy of 82.6. A CBOW model is also implemented on the MRSCC. Notebooks are provided for both models. Two notebooks are presented, each notebook presents a different architectural approach to the challenge.

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Constructed by Microsoft Research in 2011, the Sentence Completion Challenge (SCC) is a data set consisting of 1040 randomly selected sentences from Conan Doyle's Sherlock Holmes novels, each with a single word removed and replaced with a blank space token.

This paper presents a new Multi Resonant Switched-Capacitor Converters (abbreviated as MRSCCs) for high efficiency and density non-isolated DC-DC application where large voltage step down ratios are needed. Derived from Resonant Switched-Capacitor Converter (RSCC), MRSCC employs two LC resonant tanks to partially replace the flying capacitors for energy transfer. During the dead-time in ...

The MRSCC (Microsoft Research Sentence Completion Challenge) is a task which involves the prediction of missing words in a sentence over five possible alternatives. The goal of this repo is to teach AI how to answer multiple choice questions. The two approaches considered were Ngrams and Neural language models (NLM).

2022年8月24日 · In this article, series-parallel (SP) multiresonant switched-capacitor converters (MRSCCs) are proposed by incorporating resonant tanks into the traditional SP switched-capacitor converter (SCC) and adopting the on-time fixed frequency modulation.

Abstract: The traditional ladder switched-capacitor converter (SCC) has limited voltage gain range, sacrificing the overall efficiency severely to extend the voltage gain range. In this paper, Ladder multi-resonant switched-capacitor converters (MRSCC) with extended voltage gain range are proposed. By adding the multi resonance core and adopting the on-time fixed frequency modulation, a ...

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