Transformer (finetune)

Reported on 4 benchmarks across 4 tasks · 1 paper · 3 SOTA

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

Natural Language Processing3 results

Text ClassificationonSemEval 2018 Task 1E-c
Macro-F1· 2018-12-04
0.561
best: 0.578 (SpanEmo)
SOTA
Practical Text Classification With Large Pre-Trained Language Models arXiv:1812.01207
Emotion ClassificationonSemEval 2018 Task 1E-c
Macro-F1· 2018-12-04
0.561
best: 0.578 (SpanEmo)
SOTA
Practical Text Classification With Large Pre-Trained Language Models arXiv:1812.01207
Sentiment AnalysisonSST-2 Binary classification
Accuracy· 2018-12-04
90.9
best: 97.5 (T5-11B)
Practical Text Classification With Large Pre-Trained Language Models arXiv:1812.01207

Methodology1 result

ClassificationonSemEval 2018 Task 1E-c
Macro-F1· 2018-12-04
0.561
best: 0.578 (SpanEmo)
SOTA
Practical Text Classification With Large Pre-Trained Language Models arXiv:1812.01207