Fine-tuned mDeBERTa V3 model for subjectivity detection in newspaper sentences. This model was developed as part of the CLEF 2023 CheckThat! Lab Task 2: Subjectivity in News Articles.
The goal in this task is to detect whether a sentence is objective (OBJ) or subjective (SUBJ). A sentence is subjective if its content is based on or influenced by personal feelings, tastes, or opinions. Otherwise, the sentence is objective. (Antici et al., 2023).
The model was fine-tuned using a multilingual training and development dataset, for which the following (hyper)parameters were utilized:
Batch Size = 64
Max Epochs = 8
Learning Rate = 3e-5
Warmup Steps = 500
Weight Decay = 0.3
The model ranked second in the CheckThat! Lab and obtained a macro F1 of 0.81 and a SUBJ F1 of 0.81.
- Downloads last month
- 502
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.