ResNet + RoBERTa finetune

Reported on 3 benchmarks across 3 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing2 results

Text ClassificationonCivil Comments
AUROC· 2024-03-31
0.97
best: 0.9818 (RoBERTa Focal Loss)
PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning arXiv:2404.00776
Binary Classificationonkickstarter
AUROC· 2024-03-31
0.786
best: 0.81 (Trompt + OpenAI embedding)
PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning arXiv:2404.00776

Methodology1 result

ClassificationonCivil Comments
AUROC· 2024-03-31
0.97
best: 0.9818 (RoBERTa Focal Loss)
PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning arXiv:2404.00776