metadata: reword score_protocol prose off the retired score_type vocabulary (no semantic change)
Browse files- metadata.json +1 -1
metadata.json
CHANGED
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@@ -20,7 +20,7 @@
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},
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"score_protocol": {
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"reference": "lmms-eval@lmms_eval/tasks/megabench/metrics/metric_type.py:1-120 + metrics/scoring/* (45 per-task metric types: exact/near str match, set/dict equality+Jaccard, BLEU/GLEU, Levenshtein similarity, nbbox IoU, number_rel_diff_ratio, LaTeX equality, program_judge, symbolic planning, VLM-as-judge, ...) and tasks/megabench/README.md + evaluator.py — official protocol (adapted from TIGER-AI-Lab/MEGA-Bench) runs a stand-alone evaluator that dispatches each task to its own metric; core split = rule metrics, open split = GPT(-4o) judge; headline = macro mean over ~505 tasks.",
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"note": "The mm-eval copy merges test_core and test_open into one subset and stores only task_name in extra — the per-task metric/aggregation/parsing config required by the official evaluator is not shipped, so
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},
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"prompt_template": "{{ question }}",
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"mapping_from_source": {
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},
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"score_protocol": {
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"reference": "lmms-eval@lmms_eval/tasks/megabench/metrics/metric_type.py:1-120 + metrics/scoring/* (45 per-task metric types: exact/near str match, set/dict equality+Jaccard, BLEU/GLEU, Levenshtein similarity, nbbox IoU, number_rel_diff_ratio, LaTeX equality, program_judge, symbolic planning, VLM-as-judge, ...) and tasks/megabench/README.md + evaluator.py — official protocol (adapted from TIGER-AI-Lab/MEGA-Bench) runs a stand-alone evaluator that dispatches each task to its own metric; core split = rule metrics, open split = GPT(-4o) judge; headline = macro mean over ~505 tasks.",
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"note": "The mm-eval copy merges test_core and test_open into one subset and stores only task_name in extra — the per-task metric/aggregation/parsing config required by the official evaluator is not shipped, so no executable score_pipeline can reproduce the official protocol (declared unsupported). Many metrics are fractional per-sample; official headline is macro-averaged per task, not per-sample mean."
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},
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"prompt_template": "{{ question }}",
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"mapping_from_source": {
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