# High-accuracy text classification

This model was trained from scratch on an unknown dataset and achieved good performance on the evaluation set, providing effective support for related tasks.

BART-MNLI model fine-tuned on CNN news dataset for zero-shot text classification tasks

A text classification model fine-tuned on the Amazon product review sentiment analysis dataset based on the BERT base model, achieving 94.65% accuracy

A text classification model fine-tuned on the IMDB movie review dataset based on ALBERT-base-v2, used to determine sentiment orientation (positive/negative) of reviews