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- # SFT Training Config - Local Data, Multi-GPU
- # Usage: accelerate launch --config_file configs/accelerate_multi_gpu.yaml train.py sft --config configs/sft_local.yaml
- model:
- base: "Qwen/Qwen3-1.7B"
- output: "outputs/sft" # Local output
- push_to_hub: false
- dataset:
- name: "data/train" # Local path
- text_field: "text"
- split: "train"
- eval_split: 0.1
- training:
- epochs: 5
- batch_size: 2 # Per GPU, effective batch = 2 * 4 GPUs * 4 accum = 32
- gradient_accumulation_steps: 4
- learning_rate: 0.0002 # 2e-4 as float
- max_length: 512
- warmup_ratio: 0.03
- lr_scheduler: "cosine"
- ddp_find_unused_parameters: false
- lora:
- rank: 16
- alpha: 32
- dropout: 0.05
- target_modules:
- - "q_proj"
- - "k_proj"
- - "v_proj"
- - "o_proj"
- - "gate_proj"
- - "up_proj"
- - "down_proj"
- tracking:
- project: "qmd-query-expansion"
- run_name: "{day} {time}"
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