Text Classification on Amazon Review 250 labels (test)
42.98Top-1 Error RateSoftMatch/FreeMatch
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| SoftMatch/FreeMatchFramework=+SR2023.10 | 42.98 | — | — | |
| FlexMatchFramework=+SR2023.10 | 43.08 | — | — | |
| ILL# Labels=250, Backbone=Bert-Base2023.05 | 43.96 | — | — | |
| SoftMatch/FreeMatchFramework=Base2023.10 | 45.29 | — | — | |
| SoftMatch# Labels=250, Backbone=Bert-Base2023.05 | 45.29 | — | — | |
| FlexMatchFramework=Base2023.10 | 45.73 | — | — | |
| FlexMatch# Labels=250, Backbone=Bert-Base2023.05 | 45.73 | — | — | |
| SimMatch# Labels=250, Backbone=Bert-Base2023.05 | 45.91 | — | — | |
| FreeMatch# Labels=250, Backbone=Bert-Base2023.05 | 46.41 | — | — | |
| AdaMatch# Labels=250, Backbone=Bert-Base2023.05 | 46.72 | — | — | |
| Dash# Labels=250, Backbone=Bert-Base2023.05 | 47.1 | — | — | |
| FixMatch# Labels=250, Backbone=Bert-Base2023.05 | 47.61 | — | — | |
| CoMatch# Labels=250, Backbone=Bert-Base2023.05 | 48.76 | — | — | |
| Pseudo LabelFramework=+SR2023.10 | 49.13 | — | — | |
| VAT# Labels=250, Backbone=Bert-Base2023.05 | 49.83 | — | — | |
| Mean-Teacher# Labels=250, Backbone=Bert-Base2023.05 | 52.14 | — | — | |
| Pseudo LabelFramework=Base2023.10 | 53.45 | — | — | |
| Pseudo-Label# Labels=250, Backbone=Bert-Base2023.05 | 53.45 | — | — | |
| MixMatch# Labels=250, Backbone=Bert-Base2023.05 | 59.54 | — | — | |
| SemiReward (Mean)Framework=+SR2023.10 | — | 3.09 | 2.59 |