GroNLP / mdebertav3-subjectivity-arabic

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Total runs: 7
24-hour runs: 0
7-day runs: 0
30-day runs: -17
Model's Last Updated: July 12 2023
text-classification

Introduction of mdebertav3-subjectivity-arabic

Model Details of mdebertav3-subjectivity-arabic

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 Arabic development dataset, for which the following (hyper)parameters were utilized:

Batch Size    = 16
Max Epochs    = 4
Learning Rate = 5e-5
Warmup Steps  = 500
Weight Decay  = 0

The model ranked second in the CheckThat! Lab and obtained a macro F1 of 0.78 and a SUBJ F1 of 0.64.

Runs of GroNLP mdebertav3-subjectivity-arabic on huggingface.co

7
Total runs
0
24-hour runs
2
3-day runs
0
7-day runs
-17
30-day runs

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mdebertav3-subjectivity-arabic install

mdebertav3-subjectivity-arabic is an open source model from GitHub that offers a free installation service, and any user can find mdebertav3-subjectivity-arabic on GitHub to install. At the same time, huggingface.co provides the effect of mdebertav3-subjectivity-arabic install, users can directly use mdebertav3-subjectivity-arabic installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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