config/default_config.yaml

data_generation:
  design_proposals:
    count: 100
    requirement_types:
    - 新功能开发
    - 性能优化
    - 架构重构
    - API设计
    - 错误处理
  qa_pairs:
    count: 500
    diversity_threshold: 0.7
    max_code_lines: 40
    min_code_lines: 5
dataset:
  format: jsonl
  output_dir: ./data/training_data
  test_split: 0.1
  train_split: 0.8
  val_split: 0.1
evaluation:
  metrics:
  - rouge
  - bleu
  - exact_match
  sample_size: 50
gpu:
  devices:
  - 0
  - 1
  memory_per_gpu: 48
llm_api:
  batch_size: 4
  max_workers: 2
  model: Qwen/Qwen3-8B
  provider: local
model:
  base_model: Qwen/Qwen3-8B
  enable_thinking: true
  max_length: 2048
  temperature: 0.7
  thinking_budget: 4096
  top_p: 0.9
project:
  name: code_repo_training_data_generator
  version: 1.0.0
repository:
  exclude_dirs:
  - .git
  - __pycache__
  - node_modules
  - .venv
  - venv
  - build
  - dist
  languages:
  - python
  - markdown
  local_path: ./repos/Laddr
  url: https://github.com/AgnetLabs/Laddr
training:
  batch_size: 2
  bf16: true
  deepspeed_config: ./deepspeed_config_optimized.json
  eval_steps: 100
  gradient_accumulation_steps: 8
  learning_rate: 1e-3
  logging_steps: 10
  lora:
    alpha: 128
    bias: none
    dropout: 0.05
    r: 64
    target_modules:
    - q_proj
    - k_proj
    - v_proj
    - o_proj
    - gate_proj
    - up_proj
    - down_proj
  max_grad_norm: 1.0
  num_epochs: 3
  output_dir: ./output/finetuned_model
  save_steps: 100
  warmup_ratio: 0.05
  weight_decay: 0.01