KC

This model was fine-tuned on the AG News dataset (fancyzhx/agnews) for four-class news topic classification: The dataset was divided into 108,000 training examples, 12,000 validation examples, and 7,600 test examples. A random seed of 42 was used. This model is intended for English news topic classification into the four AG News categories: World, Sports, Business, and Sci/Tech. It was developed for educational purposes and experimentation with BERT adaptation methods. The model is trained on English news data and may not generalize well to other domains or languages. It only supports the four categories present in AG News. Performance on real-world data may differ from the reported…