Kedis ku xidhan hagaha · Dhexdhexaad Heerka

Kediska Daawaynta Tilmaamaha

Dib u eeg tababbarka jawaab-celinta tilmaamaha-kormeerka, marxaladaha doorashada ikhtiyaarka ah, kala duwanaanta hawsha, tijaabada LIMA, iyo qiimaynta tilmaamaha cusub.

Wadooyinka haga ee la xidhiidhaDajinta Tilmaamaha
Su'aal 1 ee 8

Iyadoo aan la hagaajin habayn, sidee buu qaabka saldhiga cayriin uga jawaabi karaa isla markiiba 'Waa maxay caasimadda Faransiiska?'

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. Iyadoo aan la hagaajin habayn, sidee buu qaabka saldhiga cayriin uga jawaabi karaa isla markiiba 'Waa maxay caasimadda Faransiiska?'
    • Had iyo jeer way diiddaa inay ka jawaabto
    • Waxay soo celinaysaa qalad
    • Waxa laga yaabaa inay ku sii socoto su'aalo badan ama qoraal la xidhiidha halkii ay ka jawaabi lahayd
    • Waxay u jawaabtaa si qumman mar kasta
  2. Hagaajinta tilmaamaha waxaa sida ugu wanaagsan loogu tilmaamay:
    • Xoojinta barashada jawaab celinta aadanaha
    • Ku tababbarka qoraalka webka ceeriin
    • Hagaajinta cabbirka heerkulka
    • Hagaajinta hagaajinta wanaagsan ee lamaanayaasha wax-barashada iyo jawaab-celinta
  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. Waa kuwee nidaamka caadiga ah ee heerarka tababarka ee kaaliyaha sheekaysiga casriga ah?
    • RLHF, ka dibna tababbarka hore, ka dibna habaynta tilmaamaha
    • Hagaajinta tilmaamaha, ka dib tababarka hore
    • Kaliya tabobar hore, wax kale ma jiraan
    • Tababar hore, ka dib habayn tilmaanta, ka dibna RLHF ikhtiyaari ah
  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