wehub-resource-sync
72 lines
6.8 KiB
Bash
72 lines
6.8 KiB
Bash
python scripts/math_scale/analyze/extract_hard_questions.py \
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--input_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.json \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.k16-fail.json \
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--maj_k 16
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python scripts/math_scale/analyze/compute_acc_by_id.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n1.tem1.0.p1.0.0-of-1.s*.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.sft-k16-fail.json \
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--id_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.k16-fail.json
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python scripts/math_scale/qwen25math_style_eval_math.py \
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--input_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n1.tem0.0.p1.0.json \
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--num_workers 1
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#{
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# "acc": 0.6292,
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# "pass@k": 0.6292,
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# "maj@k": 0.6292,
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# "correct": 3146,
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# "total": 5000
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#}
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# Compared with original: 61.4
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python scripts/math_scale/analyze/compute_acc_by_id.py \
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--input_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n1.tem0.0.p1.0.sympy_eval.json \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n1.tem0.0.p1.0.sympy_eval.sft-k16-fail.json \
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--id_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.k16-fail.json
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python scripts/math_scale/analyze/compute_acc_by_id.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/math/math.test.v1.1.0shot.n1.tem1.0.p1.0.0-of-1.s*.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.sft-k16-fail.json \
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--id_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.k16-fail.json
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python scripts/math_scale/qwen25math_style_eval_math.py \
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--input_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/math/math.test.v1.1.0shot.n1.tem0.0.p1.0.json \
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--num_workers 1
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#{
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# "acc": 0.6702,
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# "pass@k": 0.6702,
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# "maj@k": 0.6702,
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# "correct": 3351,
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# "total": 5000
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#}
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python scripts/math_scale/analyze/compute_acc_by_id.py \
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--input_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/math/math.test.v1.1.0shot.n1.tem0.0.p1.0.sympy_eval.json \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/math.test.v1.1.0shot.n1.tem0.0.p1.0.sympy_eval.sft-k16-fail.json \
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--id_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.k16-fail.json
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python scripts/math_scale/analyze/compute_acc_by_id.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mscale-v0.1-300k.process-dpo-sc.p0.5.iter1.V100.tp4dp32.v3.1.s42/checkpoint-500/math/math.test.v1.1.0shot.n1.tem1.0.p1.0.0-of-1.s*.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mscale-v0.1-300k.process-dpo-sc.p0.5.iter1.V100.tp4dp32.v3.1.s42/checkpoint-500/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.sft-k16-fail.json \
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--id_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.k16-fail.json
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python scripts/math_scale/qwen25math_style_eval_math.py \
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--input_file ../msranlpintern/reward_modeling/experiments/mathstral.mscale-v0.1-300k.process-dpo-sc.p0.5.iter1.V100.tp4dp32.v3.1.s42/checkpoint-500/math/math.test.v1.1.0shot.n1.tem0.0.p1.0.json \
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--num_workers 1
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python scripts/math_scale/analyze/compute_acc_by_id.py \
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--input_file ../msranlpintern/reward_modeling/experiments/mathstral.mscale-v0.1-300k.process-dpo-sc.p0.5.iter1.V100.tp4dp32.v3.1.s42/checkpoint-500/math/math.test.v1.1.0shot.n1.tem0.0.p1.0.sympy_eval.json \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mscale-v0.1-300k.process-dpo-sc.p0.5.iter1.V100.tp4dp32.v3.1.s42/checkpoint-500/math.test.v1.1.0shot.n1.tem0.0.p1.0.sympy_eval.sft-k16-fail.json \
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--id_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.k16-fail.json
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# mathstral.mscale-v0.1-300k.process-dpo-sc.p0.0.iter2.H100.dp16.v1.3.s42
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python scripts/math_scale/analyze/compute_acc_by_id.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mscale-v0.1-300k.process-dpo-sc.p0.0.iter2.H100.dp16.v1.3.s42/checkpoint-500/math/math.test.v1.1.0shot.n1.tem1.0.p1.0.0-of-1.s*.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mscale-v0.1-300k.process-dpo-sc.p0.0.iter2.H100.dp16.v1.3.s42/checkpoint-500/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.sft-k16-fail.json \
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--id_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.k16-fail.json
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python scripts/math_scale/qwen25math_style_eval_math.py \
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--input_file ../msranlpintern/reward_modeling/experiments/mathstral.mscale-v0.1-300k.process-dpo-sc.p0.0.iter2.H100.dp16.v1.3.s42/checkpoint-500/math/math.test.v1.1.0shot.n1.tem0.0.p1.0.json \
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--num_workers 1
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python scripts/math_scale/analyze/compute_acc_by_id.py \
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--input_file ../msranlpintern/reward_modeling/experiments/mathstral.mscale-v0.1-300k.process-dpo-sc.p0.0.iter2.H100.dp16.v1.3.s42/checkpoint-500/math/math.test.v1.1.0shot.n1.tem0.0.p1.0.sympy_eval.json \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mscale-v0.1-300k.process-dpo-sc.p0.0.iter2.H100.dp16.v1.3.s42/checkpoint-500/math.test.v1.1.0shot.n1.tem0.0.p1.0.sympy_eval.sft-k16-fail.json \
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--id_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/math/math.test.v1.1.0shot.n128.tem1.0.p1.0.k16-fail.json
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