Multi Label Text Classification On Eur Lex
Métriques
P@1
P@3
P@5
nDCG@3
nDCG@5
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | P@1 | P@3 | P@5 | nDCG@3 | nDCG@5 | Paper Title | Repository |
|---|---|---|---|---|---|---|---|
| LAHA | 74.95 | 61.48 | 50.71 | 64.89 | 59.28 | Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text Classification | |
| bert-base | - | - | 68.7 | - | 82.3 | Large-Scale Multi-Label Text Classification on EU Legislation | |
| NLP-Cap | 80.2 | 65.48 | 52.83 | 71.11 | 68.8 | Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications |
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