Cross Lingual Document Classification On 2
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy | Paper Title | Repository |
|---|---|---|---|
| XLMft UDA | 96.05 | Bridging the domain gap in cross-lingual document classification | - |
| Massively Multilingual Sentence Embeddings | 77.95 | Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond | - |
| BiLSTM (UN) | 74.52 | A Corpus for Multilingual Document Classification in Eight Languages | - |
| MultiFiT, pseudo | 89.42 | MultiFiT: Efficient Multi-lingual Language Model Fine-tuning | - |
| MultiCCA + CNN | 72.38 | A Corpus for Multilingual Document Classification in Eight Languages | - |
| BiLSTM (Europarl) | 72.83 | A Corpus for Multilingual Document Classification in Eight Languages | - |
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