# model args
model: Qwen/Qwen2.5-7B-Instruct
torch_dtype: bfloat16

tuner_type: lora
lora_rank: 8
lora_alpha: 32
target_modules: all-linear

# dataset args
dataset:
  - 'AI-ModelScope/alpaca-gpt4-data-zh#500'
  - 'AI-ModelScope/alpaca-gpt4-data-en#500'
  - 'swift/self-cognition#500'
split_dataset_ratio: 0.0
max_length: 2048
system: 'You are a helpful assistant.'
model_author: swift
model_name: swift-bot

# training args
num_train_epochs: 1
per_device_train_batch_size: 1
per_device_eval_batch_size: 1
learning_rate: 1e-4
gradient_accumulation_steps: 8
eval_steps: 50
save_steps: 50
save_total_limit: 2
logging_steps: 5
output_dir: output
warmup_ratio: 0.05
dataloader_num_workers: 4
dataset_num_proc: 4
deepspeed: zero2