video1.0<iframe src="https://www.loom.com/embed/cf7cee8151544d6c86467db16ecb858f" frameborder="0" width="1280" height="960" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>9601280Loomhttps://www.loom.com9601280https://cdn.loom.com/sessions/thumbnails/cf7cee8151544d6c86467db16ecb858f-00001.gif88.557In this video, I discuss my project of developing a custom DistilBERT model with a 768-dimensional hidden layer for semantic classification tasks. I explain what semantic classification is and how it can be used for sentiment analysis, topic categorization, intent detection, and spam detection. I also share my goal of optimizing the performance of the DistilBERT model for specific needs and the tools I used, such as the Intel Developer Cloud Notebook and the Transformers library from Hugging Face. No action is requested from the viewers.