Natural Language Processing on GLUE (100 samples subset, dev)
64.24Macro Avg ScoreMulti-CLS BERT
Evaluation Results
| Method | Links | |
|---|---|---|
| Multi-CLS BERTBackbone=BERT Large, Model Size=350.9M, K=5, lambda=0.12022.10 | 64.24 | |
| Multi-CLS BERTBackbone=BERT Large, Model Size=350.9M, K=5, lambda=02022.10 | 63.19 | |
| Multi-CLS BERTBackbone=BERT Large, Model Size=350.9M, K=5, lambda=0.52022.10 | 63.02 | |
| Multi-CLS BERTBackbone=BERT Large, Model Size=350.9M, K=5, lambda=12022.10 | 62.07 | |
| Multi-CLS BERTBackbone=BERT Base, Model Size=118.4M, K=5, lambda=0.12022.10 | 61.8 | |
| Multi-CLS BERTBackbone=BERT Base, Model Size=118.4M, K=5, lambda=02022.10 | 61.54 | |
| MTLBackbone=BERT Large, Model Size=335.2M2022.10 | 61.39 | |
| Multi-CLS BERTBackbone=BERT Base, Model Size=118.4M, K=5, lambda=0.52022.10 | 60.49 | |
| Multi-CLS BERTBackbone=BERT Base, Model Size=118.4M, K=5, lambda=12022.10 | 59.86 | |
| MTLBackbone=BERT Base, Model Size=109.5M2022.10 | 59.29 | |
| Multi-CLS BERTBackbone=BERT Large, Model Size=338.3M, K=12022.10 | 59.19 | |
| Multi-CLS BERTBackbone=BERT Base, Model Size=111.3M, K=12022.10 | 57.84 | |
| PretrainedBackbone=BERT Base, Model Size=109.5M2022.10 | 55.71 |