Ilana Tuning adanwo

Awọn idahun ati awọn alaye han bi o ṣe n mu ibeere naa.

1. Laisi yiyi itọnisọna, bawo ni awoṣe ipilẹ aise ṣe le dahun si kiakia 'Kini olu-ilu France?'
   • O nigbagbogbo kọ lati dahun
   • O pada aṣiṣe
   • O le tẹsiwaju pẹlu awọn ibeere diẹ sii tabi ọrọ ti o jọmọ dipo idahun
   • O dahun daradara ni gbogbo igba
2. Atunse itọnisọna jẹ apejuwe ti o dara julọ bi:
   • Ẹkọ imudara lati awọn esi eniyan
   • Ikẹkọ tẹlẹ lori ọrọ wẹẹbu aise
   • Siṣàtúnṣe iwọn otutu paramita
   • Abojuto itanran-yiyi lori itọnisọna-ati-idahun orisii
3. How does supervised instruction tuning differ from reward-model-based RLHF in the published InstructGPT recipe?
   • It is exactly the same optimization stage
   • It trains against reference responses, while the later preference stages use comparisons and a reward model
   • It requires no training examples
   • It only changes a sampling temperature
4. Why do instruction-tuning researchers evaluate models on held-out tasks and instructions?
   • To assess generalization beyond the examples used for training
   • To prove that every unseen task will succeed
   • To avoid checking any generated responses
   • To guarantee the same accuracy for every task mixture
5. Ewo ni aṣẹ aṣoju ti awọn ipele ikẹkọ fun oluranlọwọ iwiregbe ode oni?
   • RLHF, lẹhinna ikẹkọ iṣaaju, lẹhinna yiyi itọnisọna
   • Yiyi ilana, lẹhinna pretraining
   • Nikan pretraining, ko si ohun miiran
   • Ikẹkọ iṣaaju, lẹhinna yiyi itọnisọna, lẹhinna RLHF iyan
6. What does LIMA's curated-data experiment support as a research conclusion?
   • Exactly 1,000 examples are enough for every model and task
   • More data can never help any instruction-tuned model
   • Carefully selected small datasets can be effective in an evaluated configuration
   • Only synthetic examples can train an assistant
7. Which training stage did the original LIMA experiment omit while using its 1,000 curated prompt-response pairs?
   • Reinforcement learning and human preference modeling
   • Supervised response loss
   • A pretrained base model
   • Prompt-response examples
8. A tuned model follows the requested answer format. What does that behavior alone fail to establish?
   • That an output format was requested
   • That every factual statement in the answer is correct
   • That the model produced a response
   • That the response can be inspected