Text Classification
Transformers
Safetensors
Indonesian
xlm-roberta
clickbait
indonesian
text-embeddings-inference
Instructions to use midlyn/xlmr-clickbait-id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use midlyn/xlmr-clickbait-id with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="midlyn/xlmr-clickbait-id")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("midlyn/xlmr-clickbait-id") model = AutoModelForSequenceClassification.from_pretrained("midlyn/xlmr-clickbait-id", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Deteksi clickbait judul berita berbahasa Indonesia
Hasil fine-tuning xlm-roberta-base pada dataset CLICK-ID (klasifikasi biner: clickbait / non-clickbait).
- Max length: 64 token
- Test set (1.496 judul): accuracy 0.8389, F1 (macro) 0.8327
Model dibuat untuk keperluan penelitian skripsi. Label dataset berasal dari annotator manusia yang tidak selalu sepakat, sehingga prediksi bukan kebenaran mutlak.
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Model tree for midlyn/xlmr-clickbait-id
Base model
FacebookAI/xlm-roberta-base