python scripts/math_scale/analyze/extract_hard_questions.py \ --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 \ --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 \ --maj_k 16 python scripts/math_scale/analyze/compute_acc_by_id.py \ --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" \ --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 \ --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 python scripts/math_scale/qwen25math_style_eval_math.py \ --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 \ --num_workers 1 #{ # "acc": 0.6292, # "pass@k": 0.6292, # "maj@k": 0.6292, # "correct": 3146, # "total": 5000 #} # Compared with original: 61.4 python scripts/math_scale/analyze/compute_acc_by_id.py \ --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 \ --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 \ --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 python scripts/math_scale/analyze/compute_acc_by_id.py \ --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" \ --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 \ --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 python scripts/math_scale/qwen25math_style_eval_math.py \ --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 \ --num_workers 1 #{ # "acc": 0.6702, # "pass@k": 0.6702, # "maj@k": 0.6702, # "correct": 3351, # "total": 5000 #} python scripts/math_scale/analyze/compute_acc_by_id.py \ --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 \ --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 \ --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 python scripts/math_scale/analyze/compute_acc_by_id.py \ --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" \ --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 \ --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 python scripts/math_scale/qwen25math_style_eval_math.py \ --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 \ --num_workers 1 python scripts/math_scale/analyze/compute_acc_by_id.py \ --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 \ --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 \ --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 # mathstral.mscale-v0.1-300k.process-dpo-sc.p0.0.iter2.H100.dp16.v1.3.s42 python scripts/math_scale/analyze/compute_acc_by_id.py \ --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" \ --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 \ --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 python scripts/math_scale/qwen25math_style_eval_math.py \ --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 \ --num_workers 1 python scripts/math_scale/analyze/compute_acc_by_id.py \ --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 \ --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 \ --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