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Back to M3 — Sequences + NLP Baselines

Mini-Lab B: Sentiment + Error Slices

Acc/F1 + slice report. Deterministic F1 bar + 100-pt rubric.

71 minutesProject submission
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Assignment Instructions

Brief

Ship BoW vs frozen-mini-transformer/API sentiment baselines with accuracy/F1 + two error slices (negation, domain slang).

Dataset

Sentiment split; review-id leakage trap graded via ablation.

Starter guardrails (88)

  • Slots: BoW run, transformer/API run, metric table, slice reports, id-ablation.
  • API runs must log cost/latency per call batch.

Deterministic checks

Macro-F1 >= 0.78 on hidden slice; id-ablation present; slice reports cover the two required phenomena.

100-pt rubric

  • BoW tuning honesty: 20
  • Transformer/API comparison fairness: 20
  • F1 bar met: 15
  • Error-slice depth (2 required): 25
  • Id-leak ablation: 15
  • Cost/latency logging (API path): 5
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