Abstract
Depression is a common mental illness that involves sadness and lack of interest in all day-to-day activities.The task is to classify the social media text as signs of depression into three labels namely “not depressed”, “moderately depressed”, and “severely depressed”. We have built a system using Deep Learning Model "Transformers". Transformers provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio. The multi-class classification model used in our system is based on the ALBERT model(Lan et al., 2019). In the shared task ACL 2022, Our team SSN_MLRG3 obtained a Macro F1 score of 0.473.
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CITATION STYLE
Esackimuthu, S., Shruthi, H., Sivanaiah, R., Angel Deborah, S., Sakaya Milton, R., & Mirnalinee, T. T. (2022). SSN_MLRG3 @LT-EDI-ACL2022-Depression Detection System from Social Media Text using Transformer Models. In LTEDI 2022 - 2nd Workshop on Language Technology for Equality, Diversity and Inclusion, Proceedings of the Workshop (pp. 196–199). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.ltedi-1.26
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