Text Classification On Yelp 2
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | 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 | - |
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