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README.md
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---
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language:
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- ar
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tags:
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- subjectivity
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- newspapers
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- CLEF2023
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---
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Fine-tuned [mDeBERTa V3](https://huggingface.co/microsoft/mdeberta-v3-base) model for subjectivity detection in newspaper sentences.
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This model was developed as part of the CLEF 2023 CheckThat! Lab [Task 2: Subjectivity in News Articles](https://checkthat.gitlab.io/clef2023/task2/).
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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
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opinions. Otherwise, the sentence is objective. [(Antici et al., 2023)](https://ceur-ws.org/Vol-3370/paper10.pdf).
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The model was fine-tuned using a multilingual training and Arabic development dataset, for which the following (hyper)parameters were utilized:
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```
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Batch Size = 16
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Max Epochs = 4
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Learning Rate = 5e-5
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Warmup Steps = 500
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Weight Decay = 0
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```
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The model ranked second in the CheckThat! Lab and obtained a macro F1 of 0.78 and a SUBJ F1 of 0.64.
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