Update README.md

README.md

@@ -19,7 +19,7 @@ pipeline_tag: text-classification
 
 This model is designed for emotion recognition in Persian text. It predicts the presence of six emotions: anger, disgust, fear, sadness, happiness, and surprise, as well as the primary emotion within these categories, including an "other" category for cases when none of the specified emotions are present. The model leverages XLM-RoBERTa, a pre-trained transformer-based language model, fine-tuned on two datasets: EmoPars and ArmanEmo. It includes a Bidirectional Gated Recurrent Unit (BiGRU) layer to better capture contextual dependencies, improving performance on emotion classification tasks.
 
-- **Developed by:** Faezeh Sarlakifar, Morteza Mahdavi Mortazavi, Mehrnoush Shamsfard
+- **Developed by:** Morteza Mahdavi Mortazavi and Faezeh Sarlakifar
 - **Model type:** Text Emotion Classification (Transformer + BiGRU)
 - **Language(s):** Persian
 - **License:** MIT