# Quiz with answers — The complete pre-training pipeline ### Question 1 Solve the worked-case variant: Append a sixth token to the five-token sequence. Trace input→target pairs before and after, then state what changes in the batch without claiming that this one example improves the model. - A. “Maya reads a book” becomes five tokens. The batch uses the first four as inputs and the last four as targets. If the model assigns 0.25 to the correct target, positional loss is −log(0.25) ≈ 1.386. - B. Five tokens produce four next-token pairs; six tokens produce five. The batch gains one supervised position and one computation step, but quality still depends on filtering, diversity, and many updates. - C. A teaching pipeline omits distributed storage, security, data policies, and many production quality controls. - D. The tokenizer learns a subword vocabulary. “Maya reads a book” becomes 5 tokens for 4 words: [Maya][ reads][ a][ bo][ok] — “book” is split in two; boundaries do not follow words. **Answer: B.** Five tokens produce four next-token pairs; six tokens produce five. The batch gains one supervised position and one computation step, but quality still depends on filtering, diversity, and many updates. The correct answer executes the requested change and gives a checkable result; the other texts do not close this calculation or trace. --- ### Question 2 Which causal order correctly connects the first three stages of “The complete pre-training pipeline”? - A. Build inputs and targets → Tokenize → Collect without accepting everything - B. Tokenize → Collect without accepting everything → Build inputs and targets - C. Collect without accepting everything → Tokenize → Build inputs and targets - D. Collect without accepting everything → Build inputs and targets → Tokenize **Answer: C.** Collect without accepting everything → Tokenize → Build inputs and targets The chain follows the taught progression; reversing stages consumes a representation or state before it is produced. --- ### Question 3 If “Build inputs and targets” is removed, which diagnostic method is defensible? - A. Keep the same input, predict the first output that depends on “Build inputs and targets,” then compare the before/after trace. - B. Also change the data to amplify the difference. - C. Observe only the final output and invent the cause. - D. Conclude that the whole system fails before measuring. **Answer: A.** Keep the same input, predict the first output that depends on “Build inputs and targets,” then compare the before/after trace. One intervention and a prior prediction make the delta attributable to the removed mechanism. --- ### Question 4 Which verdict respects this session’s validity boundary? - A. The mechanism guarantees accuracy, speed, and stability for every workload. - B. One successful example proves the whole architecture is superior. - C. The mechanism name alone is enough for a production choice. - D. A teaching pipeline omits distributed storage, security, data policies, and many production quality controls. **Answer: D.** A teaching pipeline omits distributed storage, security, data policies, and many production quality controls. The correct answer bounds the conclusion; the others turn a local relation into a global guarantee. --- ### Question 5 Which evidence best matches the stated status of “The complete pre-training pipeline”? - A. The route loads without an error. - B. Established mechanisms; numerical simplifications are pedagogical. - C. Every learner opened the file. - D. The same result is assumed on every hardware target. **Answer: B.** Established mechanisms; numerical simplifications are pedagogical. Product or mechanism evidence must remain attributed and measured; availability and completion do not prove value. --- ### Question 6 When should a simpler baseline be preferred to “Loss and update”? - A. Never: the newest mechanism wins by default. - B. As soon as one memory metric falls, regardless of quality. - C. When a controlled test shows equivalent quality with lower memory, latency, or complexity. - D. As soon as the diagram contains fewer components. **Answer: C.** When a controlled test shows equivalent quality with lower memory, latency, or complexity. The choice depends on a measured trade-off on the real workload, not novelty or one isolated metric. --- ### Question 7 A learner gets the right result but cannot explain “Tokenize.” Which remediation is most useful? - A. Rebuild the first missing transformation, label its inputs and outputs, then test a neighboring case. - B. Accept the answer because the final number is correct. - C. Provide the final result a second time. - D. Change several variables and ask for an intuition. **Answer: A.** Rebuild the first missing transformation, label its inputs and outputs, then test a neighboring case. The remediation targets the first causal break and then requires transfer instead of rewarding a guessed result. --- ### Question 8 Which submission actually demonstrates the outcome “Separate pre-training, post-training, and evaluation.”? - A. A list of terms without causal relations. - B. A screenshot without values or interpretation. - C. A confident claim without a baseline or threshold. - D. A trace with starting data, transformations, observed result, boundary, and next experiment. **Answer: D.** A trace with starting data, transformations, observed result, boundary, and next experiment. The correct submission makes the reasoning reproducible and the verdict revisable by future measurement.