A Compute resources used

Table 3 shows the full results with unlikelihood training and length normalization.COP A H-Swag StoryCloze Winogrande WSC WiC FT 78 .0 PEFT methods we considered and ablate the losses. We use "Question:" and "Answer:" as Since T0 is unable to perform ICL on its own, we also compare to T5+LM, the next-step-prediction language model upon which T0 is based. Due to memory constraints and because of its improved performance, we use ensemble ICL for Table table 10 shows the T-Few ablation results. Per-dataset results of T-Few and the other top-5 methods on RAFT are shown in table 11. 18 # of Param COP A H-Swag StoryCloze WinograndeFull Model Fine-tuning 3B 81 .0