Cross Lingual Document Classification On
評価指標
Accuracy
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
モデル名 | Accuracy | Paper Title | Repository |
|---|---|---|---|
| BiLSTM (Europarl) | 71.83% | A Corpus for Multilingual Document Classification in Eight Languages | |
| MultiCCA + CNN | 81.2% | A Corpus for Multilingual Document Classification in Eight Languages | |
| XLMft UDA | 96.95% | Bridging the domain gap in cross-lingual document classification | |
| MultiFiT, pseudo | 91.62% | MultiFiT: Efficient Multi-lingual Language Model Fine-tuning | |
| Massively Multilingual Sentence Embeddings | 84.78% | Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond |
0 of 5 row(s) selected.