BERT+DK

Reported on 9 benchmarks across 3 tasks

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

Natural Language Processing6 results

Text ClassificationonSemEval 2018 Task 1E-c
Accuracy
0.591
best: 0.601 (SpanEmo)
Text ClassificationonSemEval 2018 Task 1E-c
Macro-F1
0.549
best: 0.578 (SpanEmo)
Text ClassificationonSemEval 2018 Task 1E-c
Micro-F1
0.713
Emotion ClassificationonSemEval 2018 Task 1E-c
Accuracy
0.591
best: 0.601 (SpanEmo)
Emotion ClassificationonSemEval 2018 Task 1E-c
Macro-F1
0.549
best: 0.578 (SpanEmo)
Emotion ClassificationonSemEval 2018 Task 1E-c
Micro-F1
0.713

Methodology3 results

ClassificationonSemEval 2018 Task 1E-c
Accuracy
0.591
best: 0.601 (SpanEmo)
ClassificationonSemEval 2018 Task 1E-c
Macro-F1
0.549
best: 0.578 (SpanEmo)
ClassificationonSemEval 2018 Task 1E-c
Micro-F1
0.713