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Google llc (20240256965). Instruction Fine-Tuning Machine-Learned Models Using Intermediate Reasoning Steps

From WikiPatents

Instruction Fine-Tuning Machine-Learned Models Using Intermediate Reasoning Steps

Organization Name

google llc

Inventor(s)

Hyung Won Chung of Mountain View CA US

Barret Zoph of San Francisco CA US

Dengyong Zhou of Redmond WA US

Liam Fedus of Palo Alto CA US

Shayne Longpre of Surrey CA

Le Hou of South Setauket NY US

Yi Tay of Singapore SG

Jason Weng Wei of Mountain View CA US

Siddhartha Brahma of San Jose CA US

Quoc V. Le of Sunnyvale CA US

Instruction Fine-Tuning Machine-Learned Models Using Intermediate Reasoning Steps

This abstract first appeared for US patent application 20240256965 titled 'Instruction Fine-Tuning Machine-Learned Models Using Intermediate Reasoning Steps

Original Abstract Submitted

an example method for training a machine-learned sequence processing model includes obtaining a plurality of training examples for training the machine-learned sequence processing model. for each respective training example of the plurality of training examples, the example method includes: obtaining a respective query associated with the respective training example; inputting the respective query to the machine-learned sequence processing model; obtaining, from the machine-learned sequence processing model a response to the respective query and a trace of intermediate states from the respective query to the response; evaluating the response using a ground truth response associated with the respective training example; evaluating the trace using a ground truth trace associated with the respective training example; and updating one or more parameters of the machine-learned sequence processing model based on the evaluation of the response and based on the evaluation of the trace.

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