Text Classification On Dodf Data
Métriques
Average F1
Weighted F1
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Average F1 | Weighted F1 | Paper Title | Repository |
|---|---|---|---|---|
| SVM + tf-idf (no pre-trained vocab) | 0.8755 | 0.8917 | Inferring the source of official texts: can SVM beat ULMFiT? | |
| ULMFiT (pre-trained vocab, no gradual unfreezing) | 0.8918 | 0.9257 | Inferring the source of official texts: can SVM beat ULMFiT? | |
| SVM + word counts (pre-trained vocab) | 0.8782 | 0.9049 | Inferring the source of official texts: can SVM beat ULMFiT? | |
| ULMFiT (pre-trained vocab) | 0.8374 | 0.9088 | Inferring the source of official texts: can SVM beat ULMFiT? | |
| ULMFiT (no pre-trained vocab) | 0.8469 | 0.8974 | Inferring the source of official texts: can SVM beat ULMFiT? |
0 of 5 row(s) selected.