m3hrdadfi/albert-fa-base-v2-sentiment-deepsentipers-multi

The model was trained based on Google's ALBERT BASE Version 2.0 over various writing styles from numerous subjects . It aims to classify text, such as comments, based on their emotional bias . We tested three well-known datasets for this task: Digikala user comments, SnappFood user comments and DeepSentiPers in two binary-form and multi-form types . The following table summarizes the F1 score obtained as compared to other models and architectures . The model can be used for both multi-class and binary classification, in the case of binary classification . The dataset is a balanced and augmented version of SentiPers, contains 12,138 user opinions about digital products labeled,