Text Classification On Weebit Readability
Metrics
Accuracy (5-fold)
Results
Performance results of various models on this benchmark
Model Name | Accuracy (5-fold) | Paper Title | Repository |
|---|---|---|---|
| BART-RF-T1 hybrid | 0.905 | Pushing on Text Readability Assessment: A Transformer Meets Handcrafted Linguistic Features | - |
| BERT | 0.857 | Supervised and Unsupervised Neural Approaches to Text Readability | - |
| BERT-FP-LBL | 0.927 | A Unified Neural Network Model for Readability Assessment with Feature Projection and Length-Balanced Loss | - |
| BERT + SVM (with Handcrafted Features) | 0.838 | Linguistic Features for Readability Assessment | - |
| SVM (Support Vector Machine) with Handcrafted Features | 0.803 | Text Readability Assessment for Second Language Learners | - |
0 of 5 row(s) selected.