BERTić-SentiComments-SR-Six-way is a variant of the BERTić model, fine-tuned on the task of six-way sentiment classification of Serbian short texts. It differentiates between objective-positive (+NS), objective-negative (-NS), ambiguous/mixed-positive (+M), ambiguous/mixed-negative (-M), clearly positive (+1), and clearly negative texts (-1). The model was fine-tuned for 5 epochs on the SentiComments.SR dataset.

This model was evaluated on the task of six-way sentiment classification of short texts in Serbian from the SentiComments.SR dataset and compared to multilingual BERT. Different lengths of fine-tuning were considered, ranging from 1 to 5 epochs. Linear classifiers relying on bag-of-words (BOW) and/or bag-of-embeddings (BOE) features were used as baselines.

Since the dataset is imbalanced, weighted F1 measure was utilized as the performance metric. Model fine-tuning and evaluation were performed using 10-fold stratified cross-validation. The code and data to run these experiments are available on the SentiComments.SR GitHub repository.

If you wish to use this model in your paper or project, please cite the following papers: