Text Classification On Yelp 2
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy | Paper Title | Repository |
|---|---|---|---|
| XLNet | 98.63% | XLNet: Generalized Autoregressive Pretraining for Language Understanding | - |
| BERT Finetune + UDA | 97.95% | Unsupervised Data Augmentation for Consistency Training | - |
| ULMFiT (Small data) | 97.1% | Sampling Bias in Deep Active Classification: An Empirical Study | - |
| BERT-ITPT-FiT | 98.08% | How to Fine-Tune BERT for Text Classification? | - |
| COSINE | 95.97% | Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach | - |
0 of 5 row(s) selected.