kobzaond/RLVRAMBench
RLVRAMBench Which language-model training configurations can I use with the memory I have, and how much testing does that decision require? RLVRAMBench is a measurement dataset with open evaluation tasks for a specific language-model training system. It measures memory feasibility when response generation and reinforcement-learning updates share the same graphics processors. It provides measured outcomes, fixed prediction tasks, a budgeted decision replay, reference methods, and… See the full description on the dataset page: https://huggingface.co/datasets/kobzaond/RLVRAMBench.
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1{2 "acquisition_seed": 2026091513,3 "allocation_gpus": 4,4 "comparison": "Two versus four task GPUs within the same four-GPU/64-CPU/384-GiB allocation. Matched settings and prompt seed, not necessarily identical generated responses. No causal effect of host capacity is estimated against the original panel.",5 "cost_scope": "Both periods reserve four GPUs. Report task-provisioned GPU-time (2*t2+4*t4), reservation during invocations 4*(t2+t4), and whole allocation4*T separately. Include failed/unresolved work; queue wait is separate. None is utilization-weighted time.",6 "cpus_per_task": 64,7 "data_sha256": {8 "data/codecontests/heavy_tail/test.parquet": "e9d077a023de7f80aa013c5541c33b5978a43e203ce916045bc72c4fe5c62a82",9 "data/codecontests/heavy_tail/train.parquet": "0bc6ec8fd7ef1618a604417faa4bb13cb9a0117dcffb75685b2c80c1da95f697",10 "data/gsm8k/test.parquet": "0dcd50ed32caa9d8f434d4e3ef8031bc3e49b0f823655a53be5c002e727f17dd",11 "data/gsm8k/train.parquet": "8fb13a0cd8621e5fcacdee3ffe28b3a369975478ea7ab514781f3f190cba2488",12 "data/math/test.parquet": "e0cb48b1e49874c71f4a02dff944eba08844067d98dc5bdc89c004644e6b597d",13 "data/math/train.parquet": "4aa303577e968be6f810600730c970b14be659a9ae9072cc2afefd04d67e7cb8"14 },15 "device_capacity_mib": 40960,16 "estimators": "Exact inherited predictions, donor choices and numerical peaks. No fitting, threshold change, calibration, or update from either panel's outcomes.",17 "evaluation_seeds": [18 161,19 162,20 16321 ],22 "failure_policy": "No retries, replacements, requeues or further host-memory escalation. Each pair is claimed once. Continue period two only after verified cleanup and all-device idle checks. Preserve nonlaunches and incomplete pairs.",23 "group": "estimation_host_capacity",24 "host_memory_mib": 393216,25 "implementation_sha256": {26 "memory_tuner/host_capacity_protocol.py": "9bf811457f04e02e67e31d3c9289d1155f73ee1364a233b6b77d08d86becf44b",27 "memory_tuner/run_host_capacity.py": "23f1eaf462f1825a77e91d2c8d8a4ab073f4debe0fbab134ff1863e096345d37",28 "memory_tuner/run_matched_gpu.py": "f340fb7eec5297cb675a48e267618c15d7787a42891d4a2ae4a670ec24a0cc47",29 "run_host_capacity.slurm": "59d3daa9499d1fc76d0b856be6c0a813472f488eb49f990e6ffa57ccf819b919"30 },31 "memory_margin_limit_mib": 38912,32 "model": "Qwen/Qwen2.5-7B-Instruct",33 "model_revision": "a09a35458c702b33eeacc393d103063234e8bc28",34 "numerical_reporting": "Peak error uses only configurations with three completed invocations, comparing the inherited prediction with their maximum external completed peak. Donor-copy numerical values are inherited source measurements, not refitted target estimates. Host-kill and GPU-failure peaks are not imputed or scored as completed peaks. Paired peak and runtime differences require both invocations to complete.",35 "order_seed": 2026091511,36 "original_prediction_seal_sha256": "5ed714caff922a5109346a4242545d19f2824636d0f52bb0bbd2a09b40ed4666",37 "original_protocol_sha256": "1694e447e842600612604891e7b3d036ff0791fa84c4bdbeba54ed093feefdeb",38 "outcome_rule": "All three eligible seeds required for a repeated label. Any validated GPU memory failure implies memory_failure; otherwise any completed peak above 38912 MiB implies above_margin; otherwise within_margin. Other slots are unresolved with partial eligible evidence retained.",39 "planned_pairs": 9,40 "planned_processes": 18,41 "prediction_origins": {42 "host-qwen25-7b-code_heavy_tail-c2-2gpu": "est-qwen25-7b-code_heavy_tail-c2-2gpu",43 "host-qwen25-7b-code_heavy_tail-c2-4gpu": "est-qwen25-7b-code_heavy_tail-c2-4gpu",44 "host-qwen25-7b-gsm8k-c2-2gpu": "est-qwen25-7b-gsm8k-c2-2gpu",45 "host-qwen25-7b-gsm8k-c2-4gpu": "est-qwen25-7b-gsm8k-c2-4gpu",46 "host-qwen25-7b-math-c2-2gpu": "est-qwen25-7b-math-c2-2gpu",47 "host-qwen25-7b-math-c2-4gpu": "est-qwen25-7b-math-c2-4gpu"48 },49 "primary_reporting": "Separate six-configuration inventory, all eighteen seed slots, each method's useful/failing/above-margin approvals and unscored approvals. No pooled denominator with the original panel and no population interval.",50 "protocol_version": "host-capacity-1.0",51 "randomization": "Five two-GPU-first and four four-GPU-first pairs; each workload has both orders. All six two-of-four subsets occur, with three appearing twice; each allocation ordinal appears four or five times.",52 "rationale": "Original four-GPU c2 runs were censored by the 192 GiB host limit. This one follow-up tests all three original workloads under a separately declared expanded host-resource condition; it does not replace original slots.",53 "resource_cap": {54 "gpus_per_allocation": 4,55 "idle_timeout_seconds": 180,56 "initial_allocations": 9,57 "max_concurrent_allocations": 3,58 "maximum_reserved_gpu_hours": 33,59 "payload_timeout_seconds": 1500,60 "requeue": false,61 "retries": 0,62 "wall_minutes_per_allocation": 5563 },64 "scope": "Known Qwen family and A100 stack. New seeds and host-resource condition; not blind method development, external validation, or cross-hardware transfer.",65 "specified_at_utc": "2026-09-15T18:52:11.216739+00:00",66 "stopping": "Exactly nine planned allocation claims, each capped at 55 minutes. A systemic safety or infrastructure problem may stop remaining work but cannot authorize replacement slots. Stopping must not depend on prediction correctness or favorability. Diagnosed GPU-memory failures are expected study outcomes, not by themselves infrastructure-abort grounds. Any safety or infrastructure stop is documented, and all unstarted slots remain in the inventory.",67 "subset_seed": 2026091512,68 "target_configurations": 669}70 