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In this video tutorial, the focus is on sentence transformer fine tuning. The importance of using a sentence transformer is discussed, and the process of training it on your own data is explained. The session covers the fine tuning process, the required datasets like Standford Natural Language Interface Data, and the approach used, which is similar to the Yamis-based sentence transformer. The method involves passing two sentences through the model, followed by mean pooling to generate a 768-size vector. This vector is then used for further processing to enhance performance.
