Few Shot Text Classification On Raft
Métriques
Over
ADE
Avg
B77
NIS
OSE
SOT
SRI
TAI
TC
TEH
ToS
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Over | ADE | Avg | B77 | NIS | OSE | SOT | SRI | TAI | TC | TEH | ToS | Paper Title | Repository |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
GPT-3 zero-shot | 0.378 | 0.163 | 0.292 | 0.000 | 0.572 | 0.323 | 0.628 | 0.027 | 0.362 | 0.290 | 0.303 | 0.164 | RAFT: A Real-World Few-Shot Text Classification Benchmark | |
T-Few | 0.95 | 0.804 | 0.758 | 0.695 | 0.833 | 0.676 | 0.915 | 0.508 | 0.736 | 0.879 | 0.586 | 0.75 | Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning | |
Plurality-class | 0.337 | 0.446 | 0.331 | 0.000 | 0.353 | 0.164 | 0.271 | 0.493 | 0.344 | 0.391 | 0.366 | 0.471 | RAFT: A Real-World Few-Shot Text Classification Benchmark | |
GPT-2 | 0.498 | 0.600 | 0.458 | 0.121 | 0.561 | 0.245 | 0.380 | 0.492 | 0.612 | 0.723 | 0.311 | 0.498 | RAFT: A Real-World Few-Shot Text Classification Benchmark | |
AdaBoost | 0.838 | 0.543 | 0.514 | 0.023 | 0.626 | 0.475 | 0.455 | 0.506 | 0.556 | 0.625 | 0.443 | 0.560 | RAFT: A Real-World Few-Shot Text Classification Benchmark | |
BART MNLI zero-shot | 0.462 | 0.234 | 0.382 | 0.332 | 0.615 | 0.360 | 0.644 | 0.026 | 0.469 | 0.400 | 0.543 | 0.122 | RAFT: A Real-World Few-Shot Text Classification Benchmark | |
GPT-3 | 0.937 | 0.686 | 0.627 | 0.299 | 0.679 | 0.431 | 0.769 | 0.516 | 0.656 | 0.821 | 0.526 | 0.574 | RAFT: A Real-World Few-Shot Text Classification Benchmark | |
GPT-Neo | 0.681 | 0.452 | 0.481 | 0.149 | 0.408 | 0.343 | 0.406 | 0.493 | 0.605 | 0.636 | 0.554 | 0.565 | RAFT: A Real-World Few-Shot Text Classification Benchmark | |
Human (crowdsourced) | 0.917 | 0.830 | 0.735 | 0.607 | 0.857 | 0.646 | 0.908 | 0.468 | 0.609 | 0.897 | 0.722 | 0.627 | RAFT: A Real-World Few-Shot Text Classification Benchmark |
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