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dbmdz/bert-base-turkish-cased on spoken Turkish YouTube transcripts.| Metric | Score |
|---|---|
| Macro F1 | 0.84 |
| Accuracy | 0.86 |
| Level | Precision | Recall | F1 |
|---|---|---|---|
| A1 | 0.98 | 0.96 | 0.97 |
| A2 | 0.89 | 0.82 | 0.85 |
| B1 | 0.62 | 0.77 | 0.69 |
| B2 | 0.76 | 0.71 | 0.73 |
| C1 | 0.79 | 0.88 | 0.83 |
| C2 | 1.00 | 0.95 | 0.97 |
1from transformers import pipeline
2
3classifier = pipeline(
4 "text-classification",
5 model="crklih/turkish-cefr-classifier"
6)
7
8result = classifier("Osmanlı Devleti'nin çöküşü çok boyutlu bir süreçtir.")
9# [{'label': 'B2', 'score': 0.95}]| Level | Description |
|---|---|
| A1 | Beginner — basic words and simple phrases |
| A2 | Elementary — simple sentences on everyday topics |
| B1 | Intermediate — familiar topics, some complex structures |
| B2 | Upper-Intermediate — complex sentences, abstract topics |
| C1 | Advanced — academic/technical language, complex structures |
| C2 | Proficient — near-native, nuanced, rare vocabulary |