Text Classification On Yahoo Answers
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | Accuracy | Paper Title | Repository |
|---|---|---|---|
| CCCapsNet | 73.85 | Compositional Coding Capsule Network with K-Means Routing for Text Classification | - |
| DRNN | 76.26 | Disconnected Recurrent Neural Networks for Text Categorization | - |
| Seq2CNN(50) | 55.39 | Abstractive Text Classification Using Sequence-to-convolution Neural Networks | - |
| BERT-ITPT-FiT | 77.62 | How to Fine-Tune BERT for Text Classification? | - |
| FastText | 72.3 | Bag of Tricks for Efficient Text Classification | - |
| DNC+CUW | 74.30 | Learning to Remember More with Less Memorization | - |
| EXAM | 74.8 | Explicit Interaction Model towards Text Classification | - |
| ULMFiT (Small data) | 74.3 | Sampling Bias in Deep Active Classification: An Empirical Study | - |
| SWEM-concat | 73.53 | Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms | - |
| DELTA (HAN) | 75.1 | DELTA: A DEep learning based Language Technology plAtform | - |
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