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| """Sidecar model-evaluation design for culturally specific music tagging.""" | |
| from __future__ import annotations | |
| from typing import Any | |
| MODEL_CANDIDATES: list[dict[str, Any]] = [ | |
| { | |
| "id": "laion/clap-htsat-unfused", | |
| "role": "current_zero_shot_baseline", | |
| "canonical_tags_mutated": False, | |
| "notes": "Keep as candidate evidence until evaluated per taxonomy dimension.", | |
| }, | |
| { | |
| "id": "OpenMuQ/MuQ-MuLan-large", | |
| "role": "zero_shot_music_text_candidate", | |
| "canonical_tags_mutated": False, | |
| "notes": "Most relevant drop-in zero-shot candidate; evaluate as sidecar first.", | |
| }, | |
| { | |
| "id": "m-a-p/MERT-v1-330M", | |
| "role": "embedding_candidate", | |
| "canonical_tags_mutated": False, | |
| "notes": "Use embeddings for linear probes or nearest-neighbor review labels, not direct tags.", | |
| }, | |
| { | |
| "id": "OpenMuQ/MuQ-large-msd-iter", | |
| "role": "embedding_candidate", | |
| "canonical_tags_mutated": False, | |
| "notes": "Alternative music foundation embedding model for supervised probes.", | |
| }, | |
| ] | |
| EVALUATION_DIMENSIONS = [ | |
| "genre_family", | |
| "genre_subtype", | |
| "instrumentation", | |
| "vocal_configuration", | |
| "vocal_technique", | |
| "mood", | |
| "arrangement_aesthetic", | |
| "recording_context", | |
| ] | |
| METRICS = [ | |
| "top1_accuracy_for_single_select", | |
| "top3_recall_for_review_candidates", | |
| "precision_at_emitted_threshold", | |
| "false_positive_examples", | |
| "abstention_rate", | |
| ] | |
| def model_eval_plan() -> dict[str, Any]: | |
| return { | |
| "canonical_tags_mutated": False, | |
| "minimum_reviewed_tracks": 30, | |
| "preferred_reviewed_tracks": 60, | |
| "candidates": MODEL_CANDIDATES, | |
| "dimensions": EVALUATION_DIMENSIONS, | |
| "metrics": METRICS, | |
| "decision_rule": ( | |
| "Promote a model per dimension only when it improves reviewed-label " | |
| "precision/recall over CLAP and produces inspectable false-positive examples." | |
| ), | |
| } | |