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Few Shot Text Classification On Raft

Metrics

Over

ADE

Avg

B77

NIS

OSE

SOT

SRI

TAI

TC

TEH

ToS

Results

Performance results of various models on this benchmark

													Paper Title	Repository
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
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
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
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
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
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
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 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
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

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Few Shot Text Classification On Raft | SOTA | HyperAI