chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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import json
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import argparse
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from glob import glob
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import os
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import sys
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import collections
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from multiprocessing import Pool
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from tqdm import tqdm
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from functools import partial
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sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
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from data.mathscale.util import mathscale_is_equiv
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def counting_partial_response_value(preds, label):
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assert isinstance(preds, list), preds
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v = 0
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for pred in preds:
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res = mathscale_is_equiv(pred, label)[0]
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if res:
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v += 1
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return v
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def parse_value(v, binary: bool):
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if binary:
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return 1 if v > 0 else 0
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return v
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def _process_response_worker(item):
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item_id, resp_id, prefix_id = item["prefix_id"].split("_")
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prefix = item["prefix"]
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if "mscale-v0.1" in item_id:
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pass
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elif "numina" not in item_id:
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item_id = int(item_id)
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if not item["label"]:
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return item_id, {}
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if item["pred"] == "":
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return item_id, {}
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if item["pred"] == "failed extracting answer from completion":
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return item_id, {}
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v = len([1 for res in item["res"] if res])
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return item_id, {"v": v, "prefix": prefix}
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def _process_trajectories_worker(item, binary: bool):
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item_id, trajectories = item
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outputs = {
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"idx": item_id
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}
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trajectory_pairs = [(traj["v"], traj["prefix"]) for traj in trajectories]
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prefix_vis = set()
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values = []
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prefixes = []
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for v, prefix in trajectory_pairs:
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if prefix in prefix_vis:
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continue
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values.append(parse_value(v, binary))
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prefixes.append(prefix)
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prefix_vis.add(prefix)
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outputs[f"value"] = values
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outputs[f"prefix"] = prefixes
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return outputs
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def merge_key(item, value):
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assert isinstance(item, list)
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if isinstance(value, list):
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item = item + value
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else:
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item.append(value)
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return item
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def merge_seed_sampled_data(data, id_field="id"):
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id2data = {}
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for item in data:
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if item[id_field] not in id2data:
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id2data[item[id_field]] = item
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continue
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tmp = id2data[item[id_field]]
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if isinstance(tmp["response"], str):
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tmp["response"] = [tmp["response"]]
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if not isinstance(tmp["res"], list):
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tmp["res"] = [tmp["res"]]
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if not isinstance(tmp["pred"], list):
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tmp["pred"] = [tmp["pred"]]
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tmp["response"] = merge_key(tmp["response"], item["response"])
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tmp["res"] = merge_key(tmp["res"], item["res"])
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tmp["pred"] = merge_key(tmp["pred"], item["pred"])
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assert isinstance(tmp["pred"], list), tmp["pred"]
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id2data[item[id_field]] = tmp
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return list(id2data.values())
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--input_file", type=str)
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parser.add_argument("--output_file", type=str)
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parser.add_argument("--binary", default=False, action="store_true")
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parser.add_argument("--num_workers", type=int, default=8)
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args = parser.parse_args()
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print("Collecting data...")
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if os.path.exists(args.input_file):
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data = json.load(open(args.input_file))
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else:
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data = []
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for file in sorted(glob(args.input_file)):
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if ".metrics" in file:
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continue
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print(file)
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try:
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sub_data = json.load(open(file))
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except:
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print(f"Warning: {file}l")
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sub_data = [json.loads(line) for line in open(f"{file}l").readlines()]
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data += sub_data
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data = merge_seed_sampled_data(data)
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item_id2partial_trajectories = collections.defaultdict(list)
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missing = 0
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with Pool(args.num_workers) as pool:
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inputs = []
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for item in data:
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inputs.append(item)
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for item_id, result in tqdm(pool.imap_unordered(_process_response_worker, inputs), total=len(inputs)):
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if len(result) == 0:
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missing += 1
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continue
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item_id2partial_trajectories[item_id].append(result)
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shoot_cnt = collections.Counter()
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for item_id, trajectories in item_id2partial_trajectories.items():
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for traj in trajectories:
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shoot_cnt[traj["v"]] += 1
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print(shoot_cnt)
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print(f"Missing {missing} items in the response data.")
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outputs = []
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cnt = collections.Counter()
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with Pool(args.num_workers) as pool:
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inputs = [(item_id, trajectories) for item_id, trajectories in item_id2partial_trajectories.items()]
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_annotate = partial(_process_trajectories_worker, binary=args.binary)
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for result in tqdm(pool.imap_unordered(_annotate, inputs), total=len(inputs)):
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outputs.append(result)
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cnt.update(result["value"])
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print(cnt)
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json.dump(outputs, open(args.output_file, "w"), indent=2)
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if __name__ == '__main__':
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main()
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"""
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>>> python scripts/math_scale/construct_process_rm_sample_gd.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/mathscale4o/split-512/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.*-of-512.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.process_rm_gd.binary.local.json \
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--binary --num_workers 24
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Counter({0: 1243140, 3: 916473, 2: 442815, 1: 435687})
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Missing 74 items in the response data.
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Counter({1: 1793986, 0: 1242775})
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>>> python scripts/math_scale/construct_process_rm_sample_gd.py \
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--input_file "../msranlpintern/share/models/llama3.1_8b_mathscale4o/model_lr1e-5_batch512_epochs3_gpus8_linearSchedule/mathscale4o/split-512/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.*-of-512.json" \
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--output_file ../msranlpintern/share/models/llama3.1_8b_mathscale4o/model_lr1e-5_batch512_epochs3_gpus8_linearSchedule/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.process_rm_gd.binary.local.json \
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--binary --num_workers 24
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Counter({0: 1103040, 3: 908168, 2: 435088, 1: 427143})
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Missing 0 items in the response data.
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Counter({1: 1769112, 0: 1102585})
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>>> python scripts/math_scale/construct_process_rm_sample_gd.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/mathscale4o/split-512/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.*-of-512.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.process_rm_gd.local.json \
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--num_workers 24
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Counter({0: 1243140, 3: 916473, 2: 442815, 1: 435687})
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Missing 74 items in the response data.
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Counter({0: 1242779, 3: 915927, 2: 442573, 1: 435482})
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>>> python scripts/math_scale/construct_process_rm_sample_gd.py \
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--input_file "../msranlpintern/share/models/llama3.1_8b_mathscale4o/model_lr1e-5_batch512_epochs3_gpus8_linearSchedule/mathscale4o/split-512/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.*-of-512.json" \
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--output_file ../msranlpintern/share/models/llama3.1_8b_mathscale4o/model_lr1e-5_batch512_epochs3_gpus8_linearSchedule/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.process_rm_gd.local.json \
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--num_workers 24
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>>> python scripts/math_scale/construct_process_rm_sample_gd.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/mathscale4o/split-512/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.*-of-512.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.process_rm_gd.local.json \
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--num_workers 24
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Counter({0: 1013210, 3: 660151, 2: 306372, 1: 305458})
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Missing 0 items in the response data.
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Counter({0: 1012382, 3: 659126, 2: 305949, 1: 305153})
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>>> python scripts/math_scale/construct_process_rm_sample_gd.py \
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--input_file "../msranlpintern/reward_modeling/experiments/llama3.1.8b.mathscale4o.process-dpo.iter0.A100.dp8.v2.2.s42/checkpoint-1200/mathscale4o/split-512/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.*-of-512.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/llama3.1.8b.mathscale4o.process-dpo.iter0.A100.dp8.v2.2.s42/checkpoint-1200/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.prefix_completion.n3.tem1.0.p0.9.process_rm_gd.local.json \
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--num_workers 24
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Counter({0: 950765, 3: 748413, 2: 353782, 1: 336295})
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Missing 0 items in the response data.
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Counter({0: 950541, 3: 747952, 2: 353608, 1: 336155})
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"""
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