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mdebertav3-subjectivity-multilingual
GroNLP/mdebertav3-subjectivity-multilingual
mdebertav3-subjectivity-multilingual is a text classification model from GroNLP. Use it when you need a label for a piece of text. It is set up for transformers.
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.
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Model card
From the Hugging Face model README
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.
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- Created
- Jul 12, 2023
- Updated
- Sep 11, 2023