Cross Lingual Document Classification On 1
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| MultiCCA + CNN | 72.5 | A Corpus for Multilingual Document Classification in Eight Languages | |
| BiLSTM (UN) | 69.5 | A Corpus for Multilingual Document Classification in Eight Languages | |
| XLMft UDA | 96.8 | Bridging the domain gap in cross-lingual document classification | |
| MultiFiT, pseudo | 79.1 | MultiFiT: Efficient Multi-lingual Language Model Fine-tuning | |
| BiLSTM (Europarl) | 66.65 | A Corpus for Multilingual Document Classification in Eight Languages | |
| Massively Multilingual Sentence Embeddings | 77.33 | Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond |
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