Results. We make the following observations
from the results in Table 3. SELF-INSTRUCT boosts
theinstruction-followingabilityof GPT3 byalarge
margin. The vanilla GPT3 model basically can-
not follow human instructions at all. Upon manual
analysis, we ﬁnd that it usually generates irrele-
vant and repetitive text, and does not know when
to stop generation. Compared with other mod-
els that are not speciﬁcally trained for SUPERNI,
GPT3SELF-INST achieves better performance than T0
or the GPT3 ﬁnetuned on the T0 training set, which
takes tremendous human labeling eﬀorts. Notably,
GPT3SELF-INST alsonearlymatchestheperformance
of InstructGPT001, which is trained with private
user data and human-annotated labels.
Models trained on SUPERNI training set still
achieve better performance on its evaluation set,
which we attribute to the similar instruction style
and formatting. However, we show that SELF-
INSTRUCT stillbringsinadditionalgainswhencom-
SELF-INSTRUCT- Aligning Language Model with Self Generated Instructions