NLP Classification on WebNLP
79.5S2 Test AccuracyIndividual
Evaluation results
| Method | Links | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IndividualBase Model=BERT2022.10 | 79.5 | — | — | 0 | 79.5 | 0 | 79.5 | 0 | 79.5 | 0 | 79.5 | 0 | |
| MultitaskBase Model=BERT2022.10 | 77.2 | — | — | 0 | 77.2 | 0 | 77.2 | 0 | 77.2 | 0 | 77.2 | 0 | |
| EXSSNETBase Model=BERT, Classification Head=CNN-based2022.10 | 77 | — | — | 0 | 77.1 | 0 | 76.7 | 0 | 76.9 | 0 | 76.9 | 0 | |
| MultiAdaptBERTBase Model=BERT2022.10 | 76.7 | — | — | 0 | 76.7 | 0 | 76.7 | 0 | 76.7 | 0 | 76.7 | 0 | |
| SSNETBase Model=BERT, Classification Head=CNN-based2022.10 | 76.3 | — | — | 0.8 | 76.3 | 0.8 | 76.4 | 0.3 | 76.3 | 0.3 | 76.3 | 0.6 | |
| LAMOLBase Model=BERT2022.10 | 76.1 | — | — | — | 76.1 | — | 77.2 | — | 76.7 | — | 76.5 | — | |
| RegularizationBase Model=BERT2022.10 | 76 | — | — | 2.8 | 74.9 | 3.8 | 76.4 | 1.8 | 76.5 | 2 | 76 | 2.6 | |
| IDBRBase Model=BERT2022.10 | 75.9 | — | — | 2.7 | 75.4 | 3.5 | 76.5 | 1.6 | 76.4 | 1.9 | 76 | 2.4 | |
| SupSupBase Model=BERT, Classification Head=CNN-based2022.10 | 75.9 | — | — | 0 | 76.1 | 0 | 76 | 0 | 75.9 | 0 | 76 | 0 | |
| ReplayBase Model=BERT2022.10 | 75.1 | — | — | 3.1 | 74.6 | 3.5 | 75.2 | 2.2 | 75.7 | 3.1 | 75.1 | 3 | |
| MBPA++Base Model=BERT2022.10 | 74.9 | — | — | — | 73.1 | — | 74.9 | — | 74.1 | — | 74.3 | — | |
| AdaptBERT + ReplayBase Model=BERT2022.10 | 73.2 | — | — | 3 | 74.5 | 2 | 74.5 | 2 | 74.6 | 2 | 74.2 | 2.3 | |
| Prompt TuningBase Model=BERT2022.10 | 66.3 | — | — | 0 | 66.3 | 0 | 66.3 | 0 | 66.3 | 0 | 66.3 | 0 | |
| FTBase Model=BERT2022.10 | 26.9 | — | — | 62.1 | 22.8 | 67.6 | 30.6 | 55.9 | 15.6 | 76.8 | 24 | 65.6 | |
| AdaptBERT + FTBase Model=BERT2022.10 | 20.8 | — | — | 68.4 | 19.1 | 70.9 | 23.6 | 64.5 | 14.6 | 76 | 19.6 | 70 | |
| RandomBase Model=BERT2022.10 | 7.14 | — | — | — | 7.14 | — | 7.14 | — | 7.14 | — | 7.14 | — |