Starting Qwen3.5-2B Metamath training
Output: /data/pretrained_models/Qwen3.5-2B-metamath
Effective batch size: 16
/data/home/lg/.conda/envs/verl_qwen35/lib/python3.12/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
  import pynvml  # type: ignore[import]
`torch_dtype` is deprecated! Use `dtype` instead!

Loading weights:   0%|          | 0/320 [00:00<?, ?it/s]
Loading weights: 100%|██████████| 320/320 [00:00<00:00, 8654.02it/s]
warmup_ratio is deprecated and will be removed in v5.2. Use `warmup_steps` instead.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'eos_token_id': 248046, 'pad_token_id': 248044}.
trainable params: 21,823,488 || all params: 1,903,648,576 || trainable%: 1.1464

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  9%|▊         | 250/2865 [56:06<13:03:47, 17.98s/it]{'loss': '1.135', 'grad_norm': '0.1992', 'learning_rate': '1.047e-05', 'epoch': '0.01048'}
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{'loss': '0.5072', 'grad_norm': '0.2145', 'learning_rate': '9.998e-05', 'epoch': '0.1153'}
{'loss': '0.4945', 'grad_norm': '0.1742', 'learning_rate': '9.997e-05', 'epoch': '0.1258'}
{'loss': '0.4714', 'grad_norm': '0.2223', 'learning_rate': '9.994e-05', 'epoch': '0.1362'}
{'loss': '0.4666', 'grad_norm': '0.1746', 'learning_rate': '9.991e-05', 'epoch': '0.1467'}
{'loss': '0.4509', 'grad_norm': '0.1707', 'learning_rate': '9.987e-05', 'epoch': '0.1572'}
{'loss': '0.4074', 'grad_norm': '0.1343', 'learning_rate': '9.983e-05', 'epoch': '0.1677'}
{'loss': '0.3999', 'grad_norm': '0.1777', 'learning_rate': '9.978e-05', 'epoch': '0.1782'}
{'loss': '0.4166', 'grad_norm': '0.1673', 'learning_rate': '9.972e-05', 'epoch': '0.1886'}
{'loss': '0.3702', 'grad_norm': '0.1334', 'learning_rate': '9.966e-05', 'epoch': '0.1991'}
{'loss': '0.3509', 'grad_norm': '0.1804', 'learning_rate': '9.959e-05', 'epoch': '0.2096'}
{'loss': '0.3792', 'grad_norm': '0.1462', 'learning_rate': '9.952e-05', 'epoch': '0.2201'}
{'loss': '0.328', 'grad_norm': '0.1452', 'learning_rate': '9.944e-05', 'epoch': '0.2305'}
{'loss': '0.3481', 'grad_norm': '0.1467', 'learning_rate': '9.935e-05', 'epoch': '0.241'}
{'loss': '0.33', 'grad_norm': '0.1816', 'learning_rate': '9.925e-05', 'epoch': '0.2515'}
{'loss': '0.3128', 'grad_norm': '0.1381', 'learning_rate': '9.915e-05', 'epoch': '0.262'}


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 17%|█▋        | 500/2865 [2:10:17<10:59:00, 16.72s/it]{'eval_loss': '0.3133', 'eval_runtime': '94.88', 'eval_samples_per_second': '3.278', 'eval_steps_per_second': '3.278', 'epoch': '0.262'}
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{'loss': '0.3141', 'grad_norm': '0.1683', 'learning_rate': '9.856e-05', 'epoch': '0.3144'}
{'loss': '0.2776', 'grad_norm': '0.1293', 'learning_rate': '9.842e-05', 'epoch': '0.3249'}
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{'loss': '0.287', 'grad_norm': '0.1859', 'learning_rate': '9.813e-05', 'epoch': '0.3458'}
{'loss': '0.2508', 'grad_norm': '0.1705', 'learning_rate': '9.797e-05', 'epoch': '0.3563'}
{'loss': '0.2546', 'grad_norm': '0.1316', 'learning_rate': '9.781e-05', 'epoch': '0.3668'}
{'loss': '0.2656', 'grad_norm': '0.1623', 'learning_rate': '9.764e-05', 'epoch': '0.3773'}
{'loss': '0.2632', 'grad_norm': '0.1297', 'learning_rate': '9.746e-05', 'epoch': '0.3877'}
{'loss': '0.2625', 'grad_norm': '0.1286', 'learning_rate': '9.728e-05', 'epoch': '0.3982'}
{'loss': '0.2474', 'grad_norm': '0.1588', 'learning_rate': '9.71e-05', 'epoch': '0.4087'}
{'loss': '0.2278', 'grad_norm': '0.1196', 'learning_rate': '9.69e-05', 'epoch': '0.4192'}
{'loss': '0.2332', 'grad_norm': '0.1364', 'learning_rate': '9.67e-05', 'epoch': '0.4297'}
{'loss': '0.2506', 'grad_norm': '0.1514', 'learning_rate': '9.65e-05', 'epoch': '0.4401'}
{'loss': '0.2079', 'grad_norm': '0.1099', 'learning_rate': '9.629e-05', 'epoch': '0.4506'}
{'loss': '0.2145', 'grad_norm': '0.1198', 'learning_rate': '9.607e-05', 'epoch': '0.4611'}
{'loss': '0.22', 'grad_norm': '0.1268', 'learning_rate': '9.585e-05', 'epoch': '0.4716'}
{'loss': '0.2141', 'grad_norm': '0.1684', 'learning_rate': '9.562e-05', 'epoch': '0.4821'}
{'loss': '0.2053', 'grad_norm': '0.1499', 'learning_rate': '9.539e-05', 'epoch': '0.4925'}
{'loss': '0.2225', 'grad_norm': '0.1391', 'learning_rate': '9.515e-05', 'epoch': '0.503'}
{'loss': '0.2149', 'grad_norm': '0.1441', 'learning_rate': '9.49e-05', 'epoch': '0.5135'}
{'loss': '0.1997', 'grad_norm': '0.165', 'learning_rate': '9.465e-05', 'epoch': '0.524'}


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 26%|██▌       | 750/2865 [3:24:40<10:05:37, 17.18s/it]{'eval_loss': '0.1927', 'eval_runtime': '95.34', 'eval_samples_per_second': '3.262', 'eval_steps_per_second': '3.262', 'epoch': '0.524'}
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{'loss': '0.1509', 'grad_norm': '0.1192', 'learning_rate': '8.66e-05', 'epoch': '0.786'}


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 35%|███▍      | 1000/2865 [4:37:11<8:38:04, 16.67s/it]{'eval_loss': '0.1356', 'eval_runtime': '94.06', 'eval_samples_per_second': '3.307', 'eval_steps_per_second': '3.307', 'epoch': '0.786'}
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{'loss': '0.1107', 'grad_norm': '0.1041', 'learning_rate': '7.565e-05', 'epoch': '1.047'}


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{'loss': '0.07855', 'grad_norm': '0.1051', 'learning_rate': '5.093e-05', 'epoch': '1.529'}
{'loss': '0.08821', 'grad_norm': '0.09334', 'learning_rate': '5.037e-05', 'epoch': '1.54'}
{'loss': '0.08062', 'grad_norm': '0.1148', 'learning_rate': '4.98e-05', 'epoch': '1.55'}
{'loss': '0.09406', 'grad_norm': '0.08406', 'learning_rate': '4.924e-05', 'epoch': '1.561'}
{'loss': '0.07752', 'grad_norm': '0.1293', 'learning_rate': '4.867e-05', 'epoch': '1.571'}


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 70%|██████▉   | 2000/2865 [7:43:35<1:40:06,  6.94s/it]{'eval_loss': '0.06596', 'eval_runtime': '35.5', 'eval_samples_per_second': '8.761', 'eval_steps_per_second': '8.761', 'epoch': '1.833'}
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{'loss': '0.04766', 'grad_norm': '0.08582', 'learning_rate': '2.597e-05', 'epoch': '2.01'}
{'loss': '0.03826', 'grad_norm': '0.1457', 'learning_rate': '2.547e-05', 'epoch': '2.021'}
{'loss': '0.04506', 'grad_norm': '0.09275', 'learning_rate': '2.498e-05', 'epoch': '2.031'}
{'loss': '0.04905', 'grad_norm': '0.09086', 'learning_rate': '2.45e-05', 'epoch': '2.042'}
{'loss': '0.05008', 'grad_norm': '0.1173', 'learning_rate': '2.401e-05', 'epoch': '2.052'}
{'loss': '0.04058', 'grad_norm': '0.08942', 'learning_rate': '2.353e-05', 'epoch': '2.063'}
{'loss': '0.04843', 'grad_norm': '0.08561', 'learning_rate': '2.305e-05', 'epoch': '2.073'}
{'loss': '0.05441', 'grad_norm': '0.07992', 'learning_rate': '2.258e-05', 'epoch': '2.084'}
{'loss': '0.0459', 'grad_norm': '0.08846', 'learning_rate': '2.211e-05', 'epoch': '2.094'}


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{'loss': '0.04016', 'grad_norm': '0.0911', 'learning_rate': '1.164e-05', 'epoch': '2.356'}


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{'eval_loss': '0.0509', 'eval_runtime': '85.29', 'eval_samples_per_second': '3.646', 'eval_steps_per_second': '3.646', 'epoch': '2.88'}
{'loss': '0.03069', 'grad_norm': '0.0846', 'learning_rate': '3.586e-07', 'epoch': '2.891'}
{'loss': '0.03266', 'grad_norm': '0.06866', 'learning_rate': '2.942e-07', 'epoch': '2.901'}
{'loss': '0.03419', 'grad_norm': '0.09083', 'learning_rate': '2.361e-07', 'epoch': '2.912'}
{'loss': '0.03811', 'grad_norm': '0.1077', 'learning_rate': '1.844e-07', 'epoch': '2.922'}
{'loss': '0.04068', 'grad_norm': '0.08321', 'learning_rate': '1.391e-07', 'epoch': '2.933'}
{'loss': '0.04103', 'grad_norm': '0.1124', 'learning_rate': '1.002e-07', 'epoch': '2.943'}
{'loss': '0.0379', 'grad_norm': '0.072', 'learning_rate': '6.759e-08', 'epoch': '2.954'}
{'loss': '0.03996', 'grad_norm': '0.08249', 'learning_rate': '4.14e-08', 'epoch': '2.964'}
{'loss': '0.04229', 'grad_norm': '0.08522', 'learning_rate': '2.16e-08', 'epoch': '2.975'}
{'loss': '0.03814', 'grad_norm': '0.08586', 'learning_rate': '8.179e-09', 'epoch': '2.985'}
{'loss': '0.03347', 'grad_norm': '0.06642', 'learning_rate': '1.15e-09', 'epoch': '2.996'}
{'train_runtime': '3.582e+04', 'train_samples_per_second': '1.279', 'train_steps_per_second': '0.08', 'train_loss': '0.1384', 'epoch': '3'}

Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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{
  "base_model": "/data/pretrained_models/Qwen3.5-2B",
  "original_units": "/home/lg/workflow_tooluse/Flow_RL_luogan/temp/metamath/metamath-output/setmm-train-qwen35-4b-mixed-12000/setmm-proof-units.jsonl",
  "expanded_units": "/home/lg/workflow_tooluse/Flow_RL_luogan/temp/metamath/metamath-output/setmm-train-qwen35-4b-mixed-12000/setmm-expanded-units.jsonl",
  "output_dir": "/data/pretrained_models/Qwen3.5-2B-metamath",
  "merged_dir": "/data/pretrained_models/Qwen3.5-2B-metamath/merged",
  "train_examples": 15267,
  "eval_examples": 311,
  "skipped_examples": 422,
  "max_length": 6144,
  "direct_ref_mode": "same-file-distractors",
  "same_file_distractor_direct_refs": 4,
  "shuffle_direct_refs": true,
  "learning_rate": 0.0001,
  "lora_rank": 32,
  "lora_alpha": 64
}
Exception ignored in: <function ResourceTracker.__del__ at 0x71bfd1648ea0>
Traceback (most recent call last):
  File "/home/lg/.local/lib/python3.12/site-packages/multiprocess/resource_tracker.py", line 80, in __del__
  File "/home/lg/.local/lib/python3.12/site-packages/multiprocess/resource_tracker.py", line 89, in _stop
  File "/home/lg/.local/lib/python3.12/site-packages/multiprocess/resource_tracker.py", line 102, in _stop_locked
AttributeError: '_thread.RLock' object has no attribute '_recursion_count'