Open-LLaMA-3B results are much worse than reported in this repo

[XinnuoXu]

Task	Version	Metric	Value		Stderr
anli_r1	0	acc	0.3330	±	0.0149
anli_r2	0	acc	0.3320	±	0.0149
anli_r3	0	acc	0.3367	±	0.0136
arc_challenge	0	acc	0.2099	±	0.0119
		acc_norm	0.2705	±	0.0130
arc_easy	0	acc	0.2542	±	0.0089
		acc_norm	0.2517	±	0.0089
hellaswag	0	acc	0.2621	±	0.0044
		acc_norm	0.2741	±	0.0045
openbookqa	0	acc	0.1800	±	0.0172
		acc_norm	0.2500	±	0.0194
piqa	0	acc	0.5147	±	0.0117
		acc_norm	0.5011	±	0.0117
record	0	f1	0.2017	±	0.0040
		em	0.1964	±	0.0040
rte	0	acc	0.4946	±	0.0301
truthfulqa_mc	1	mc1	0.2375	±	0.0149
		mc2	0.4767	±	0.0169
wic	0	acc	0.5000	±	0.0198
winogrande	0	acc	0.5099	±	0.0140

[XinnuoXu]

It seems that the anli_* and truthfulqa_mc are similar. But the rest is -20% worse. I'm wondering the results reported in this repo for hellaswag and ARC_* are few-shot = 0 or not?

[young-geng]

Everything reported here is zero shot. Did you turn off the fast tokenizer when evaluating? There is a bug in the recent release of transformers library which causes the auto converted tokenizer to output different tokens than the original tokenizer. Therefore, when evaluating OpenLLaMA, you need to turn off the fast tokenizer.

[buzzCraft]

Is that bug still there? I thought I read somewhere that it got fixed.

[young-geng]

@buzzCraft It got fixed in the main branch of transformers but there hasn't been a release with that fix yet

[buzzCraft]

@young-geng ok,since we are on the bleeding edge of the llm field, I usually go with the dev branch.

I also want to thank you and the team for the amazing work you have done. ❤️