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A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Natural Gas Pipeline Company of America's 20-inch Indian Basin Pipeline ruptured and released approximately 31,757 MCF (31,757,000 cubic feet) of natural gas in Eddy County, New Mexico. There was no fire or injuries. [16] December 24 – A gas transmission pipeline exploded and burned, in Lyons, Nebraska. There were no injuries.
The cause of the pipeline failure was corrosion. [186] [187] January 18 – A natural gas explosion destroyed the building housing the K&W Cafeteria and the lobby of the Sheraton Motor Inn at Winston-Salem, North Carolina. Two adjoining motel wings suffered structural damage.
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That is, after pre-training, BERT can be fine-tuned with fewer resources on smaller datasets to optimize its performance on specific tasks such as natural language inference and text classification, and sequence-to-sequence-based language generation tasks such as question answering and conversational response generation.
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A 6-foot (1.8 m) break in the pipeline resulted in one of the largest inland oil spills in U.S. history (the largest was the 1991 spill near Grand Rapids, Minnesota [1]). The pipeline carries diluted bitumen (dilbit), a heavy crude oil from Canada's Athabasca oil sands to the United States. [2] Cleanup took five years. [3]