m3hrdadfi/albert-fa-base-v2-clf-persiannews

The task target is labeling texts in a supervised manner in both existing datasets DigiMag and Persian News . The total number of articles is 16,438, spread over eight different classes . The model was trained based on Google's ALBERT BASE Version 2.0 over various writing styles from numerous subjects (e.g., scientific, novels, news) with more than 3.9M documents, 73M sentences, and 1.3B words, like the way we did for ParsBERT for the Persian Language . You can download the dataset from here . The following table summarizes the F1 score obtained as compared to other models and architectures . Please cite the model in publications as the following,