modelscope / modelscope/ms-swift

seq_acc=0

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bug
Dominant language
Python
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Description

Checklist / 检查清单
  • I have searched existing issues, and this is a new bug report. / 我已经搜索过现有的 issues,确认这是一个新的 bug report。
Bug Description / Bug 描述

seq_acc始终为0

Image
How to Reproduce / 如何复现

swift sft
--model "Qwen3.5-9B"
--dataset "base_stage2/data.jsonl"
--loss_scale ignore_empty_think
--add_non_thinking_prefix true
--split_dataset_ratio 0
--packing true
--tuner_type full
--num_train_epochs 200
--save_steps 100
--per_device_train_batch_size 4
--learning_rate 5e-7
--freeze_vit false
--freeze_aligner false
--gradient_accumulation_steps $(expr 256 / ( $NNODES * $NPROC_PER_NODE ))
--save_strategy steps
--save_total_limit 2
--logging_steps 1
--lr_scheduler_type cosine
--max_length 5120
--output_dir "${OUTPUT_DIR}"
--report_to tensorboard
--warmup_ratio 0.1
--dataloader_num_workers 8
--dataset_num_proc 2
--use_liger_kernel true
--deepspeed zero2
--torch_dtype bfloat16
--attn_impl flash_attn \

Additional Information / 补充信息

No response

Contributor guide

Open the contributing guide

First steps

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  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No source files or tests are identified. Start by reproducing the supplied swift sft command, then locate the seq_acc metric's calculation and logging path and compare them with this configuration. Done means identifying why the metric remains zero and adding a regression check or correction that demonstrates the expected value.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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