Sentiment Classification on Yelp5 (test)
98.5AccuracyICL-gold
Evaluation Results
| Method | Links | |
|---|---|---|
| ICL-goldPrompting Method=Direct, Backbone=GPT-3, Oracle=true2022.12 | 98.5 | |
| Z-ICLPrompting Method=Direct, Backbone=GPT-32022.12 | 97.7 | |
| No-demosPrompting Method=Direct, Backbone=GPT-32022.12 | 96.4 | |
| ICL-randomPrompting Method=Direct, Backbone=GPT-3, Oracle=true2022.12 | 93.7 | |
| ICL-goldPrompting Method=Channel, Backbone=GPT-3, Oracle=true2022.12 | 91.7 | |
| ICL-randomPrompting Method=Channel, Backbone=GPT-3, Oracle=true2022.12 | 90.4 | |
| No-demosPrompting Method=Channel, Backbone=GPT-32022.12 | 88 | |
| Z-ICLPrompting Method=Channel, Backbone=GPT-32022.12 | 87.6 | |
| Majority2022.12 | 50 | |
| ICL-randomModel=GPT-J, Prompting=Channel, Training data access=true2022.12 | 48 | |
| ICL-goldModel=GPT-J, Prompting=Direct, Training data access=true2022.12 | 47.5 | |
| ICL-goldModel=GPT-J, Prompting=Channel, Training data access=true2022.12 | 47.4 | |
| Z-ICLModel=GPT-J, Prompting=Channel, Training data access=false2022.12 | 44.2 | |
| ICL-randomModel=GPT-J, Prompting=Direct, Training data access=true2022.12 | 43.5 | |
| ICL-goldModel=GPT-NeoX, Prompting=Channel, Training data access=true2022.12 | 43.5 | |
| ICL-randomModel=GPT-NeoX, Prompting=Channel, Training data access=true2022.12 | 43.5 | |
| Naive Z-ICLModel=GPT-J, Prompting=Channel, Training data access=false2022.12 | 41.8 | |
| ICL-randomModel=GPT-NeoX, Prompting=Direct, Training data access=true2022.12 | 41.3 | |
| Naive Z-ICLModel=GPT-J, Prompting=Direct, Training data access=false2022.12 | 41.2 | |
| Z-ICLModel=GPT-J, Prompting=Direct, Training data access=false2022.12 | 40.8 | |
| ICL-goldModel=GPT-NeoX, Prompting=Direct, Training data access=true2022.12 | 40.6 | |
| Random inputsModel=GPT-J, Prompting=Channel, Training data access=false2022.12 | 40.5 | |
| Z-ICLModel=GPT-NeoX, Prompting=Channel, Training data access=false2022.12 | 39.9 | |
| Naive Z-ICLModel=GPT-NeoX, Prompting=Direct, Training data access=false2022.12 | 39.1 | |
| Z-ICLModel=GPT-NeoX, Prompting=Direct, Training data access=false2022.12 | 38.6 | |
| Random inputsModel=GPT-NeoX, Prompting=Direct, Training data access=false2022.12 | 37.1 | |
| Naive Z-ICLModel=GPT-NeoX, Prompting=Channel, Training data access=false2022.12 | 36.9 | |
| No-demosModel=GPT-J, Prompting=Channel, Training data access=false2022.12 | 36.6 | |
| Random inputsModel=GPT-J, Prompting=Direct, Training data access=false2022.12 | 36.4 | |
| Random inputsModel=GPT-NeoX, Prompting=Channel, Training data access=false2022.12 | 29.1 | |
| No-demosModel=GPT-J, Prompting=Direct, Training data access=false2022.12 | 28.7 | |
| No-demosModel=GPT-NeoX, Prompting=Channel, Training data access=false2022.12 | 28.6 | |
| No-demosModel=GPT-NeoX, Prompting=Direct, Training data access=false2022.12 | 21.3 | |
| MajorityTraining data access=false2022.12 | 20 |