sft_local.yaml 878 B

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  1. # SFT Training Config - Local Data, Multi-GPU
  2. # Usage: accelerate launch --config_file configs/accelerate_multi_gpu.yaml train.py sft --config configs/sft_local.yaml
  3. model:
  4. base: "Qwen/Qwen3-1.7B"
  5. output: "outputs/sft" # Local output
  6. push_to_hub: false
  7. dataset:
  8. name: "data/train" # Local path
  9. text_field: "text"
  10. split: "train"
  11. eval_split: 0.1
  12. training:
  13. epochs: 5
  14. batch_size: 2 # Per GPU, effective batch = 2 * 4 GPUs * 4 accum = 32
  15. gradient_accumulation_steps: 4
  16. learning_rate: 0.0002 # 2e-4 as float
  17. max_length: 512
  18. warmup_ratio: 0.03
  19. lr_scheduler: "cosine"
  20. ddp_find_unused_parameters: false
  21. lora:
  22. rank: 16
  23. alpha: 32
  24. dropout: 0.05
  25. target_modules:
  26. - "q_proj"
  27. - "k_proj"
  28. - "v_proj"
  29. - "o_proj"
  30. - "gate_proj"
  31. - "up_proj"
  32. - "down_proj"
  33. tracking:
  34. project: "qmd-query-expansion"
  35. run_name: "{day} {time}"