Text Classification On Onestopenglish
Metrics
Accuracy (5-fold)
Results
Performance results of various models on this benchmark
Model Name | Accuracy (5-fold) | Paper Title | Repository |
|---|---|---|---|
| NPRM-BERT | 0.979 | A Neural Pairwise Ranking Model for Readability Assessment | |
| RoBERTa-RF-T1 hybrid | 0.990 | Pushing on Text Readability Assessment: A Transformer Meets Handcrafted Linguistic Features | |
| SMO (Sequential Minimal Optimization) | 0.781 | OneStopEnglish corpus: A new corpus for automatic readability assessment and text simplification | - |
| HAN (Hierarchical Attention Network) | 0.787 | Supervised and Unsupervised Neural Approaches to Text Readability | |
| Logistic Regression | 0.744 | BERT Embeddings for Automatic Readability Assessment |
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