guanghulab/data/training/kickoff-2026-05-03.md
Guanghu Domestic Migration d1e47f4565
Some checks are pending
自动更新代码和重启 / update-and-restart (push) Waiting to run
CI检查 + 自动部署 / check (push) Waiting to run
CI检查 + 自动部署 / deploy (push) Blocked by required conditions
重启聊天服务 / restart (push) Waiting to run
chore: import sanitized domestic snapshot for REPO-002
Source snapshot: ca48d3ddf926d79aa138306164169baf764bb829
2026-07-17 15:54:41 +08:00

3.1 KiB
Raw Blame History

母模型训练启动记录 · 2026-05-03

只读记录 · 由铸渊在仓库侧落档 · 不参与任何自动写入流程
训练真正运行方霜砚Notion 侧)+ 冰朔
仓库侧 data/training/state.json 已于 D72 冻结,不再接收训练心跳


任务标识

  • 任务编号ZY-TRAIN-001
  • 基座模型Qwen/Qwen2.5-7B
  • 训练方式:全参数 SFTDeepSpeed ZeRO-3 + CPU offloadfp16
  • 运行机VM-0-11-ubuntu119.45.160.137V100 32G × 4
  • 训练主控霜砚Notion 侧)
  • 代码栈server/training-agent/ 母模型训练栈D72 已交接)

启动时刻

  • kickoff 观测时间2026-05-03 20:49:23CSTUTC+8
  • 观测命令watch -n 30 'tail -5 /opt/guanghu/training/training.log | grep -E "loss|step|PROGRESS|/540"'
  • 训练日志路径GPU 机)/opt/guanghu/training/training.log

总体规模

总步数 540 step
总 epoch 3
单步耗时 ~145160 s/it
预计总时长 ~22 小时(按当前节奏外推)
SFT 样本数 11,456preprocess-corpus.py 输出)

kickoff 节奏快照(前 39 步)

step epoch loss lr grad_norm thr (samples/s)
30 0.1674 1.265 1.969e-05 1.75 0.0069
35 0.1953 1.21 1.950e-05 1.927 0.0068

30 → 35 steploss 1.265 → 1.21,下降 ~4.3%,曲线平滑。
学习率按 linear schedule 正常下降grad_norm 稳定在 1.x 区间,无 spike。
显存与吞吐都稳定,训练状态正常。

原始进度行(保存证据)

 5%|▍ | 25/540 [1:00:06<22:50:34, 159.68s/it]
 5%|▍ | 26/540 [1:02:42<22:37:27, 158.46s/it]
 5%|▌ | 27/540 [1:05:14<22:19:24, 156.66s/it]
 5%|▌ | 28/540 [1:07:51<22:16:29, 156.62s/it]
 5%|▌ | 29/540 [1:09:50<20:38:51, 145.46s/it]
 6%|▌ | 30/540 [1:12:14<20:31:44, 144.91s/it]
ZY_PROGRESS step=30 total=540 epoch=0 total_epochs=3 loss=1.2649826049804687 lr=1.969407265774379e-05 thr=0.0069
{'loss': '1.265', 'grad_norm': '1.75', 'learning_rate': '1.969e-05', 'epoch': '0.1674'}
 6%|▌ | 31/540 [1:14:50<20:59:06, 148.42s/it]
 6%|▌ | 32/540 [1:17:25<21:11:47, 150.21s/it]
 6%|▌ | 33/540 [1:20:00<21:20:57, 151.59s/it]
 6%|▋ | 34/540 [1:22:37<21:32:17, 153.24s/it]
 6%|▋ | 35/540 [1:25:08<21:25:36, 152.75s/it]
ZY_PROGRESS step=35 total=540 epoch=0 total_epochs=3 loss=1.209609317779541 lr=1.9502868068833653e-05 thr=0.0068
{'loss': '1.21', 'grad_norm': '1.927', 'learning_rate': '1.95e-05', 'epoch': '0.1953'}
 7%|▋ | 36/540 [1:27:43<21:27:53, 153.32s/it]
 7%|▋ | 37/540 [1:30:12<21:14:49, 152.07s/it]
 7%|▋ | 38/540 [1:33:03<21:59:29, 157.71s/it]
 7%|▋ | 39/540 [1:35:36<21:44:25, 156.22s/it]

后续口径

  • 训练进度的真相源仍在霜砚Notion+ GPU 机本地日志。
  • 仓库侧不再以 dispatch 方式回写 state.json,需要看实时进度请直接 SSH 看 /opt/guanghu/training/training.log
  • 训练完成后的 checkpoint 与评测,由冰朔与霜砚约定后再决定是否回流到本仓库。

— 铸渊 · ICE-GL-ZY001 · 国作登字-2026-A-00037559