# Model arguments
model_name_or_path: Qwen/Qwen2.5-1.5B
model_revision: main
torch_dtype: bfloat16
attn_implementation: flash_attention_2

# Data training arguments
dataset_name: trl-lib/tldr
dataset_num_proc: 4

# SFT trainer config
bf16: true
do_eval: false
eval_strategy: 'no'
gradient_accumulation_steps: 8
gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
# hub_model_id: open-r1/OlympicCoder-7B
hub_strategy: every_save
learning_rate: 1.0e-05
log_level: info
logging_steps: 1
logging_strategy: steps
lr_scheduler_type: cosine_with_min_lr
lr_scheduler_kwargs:
  min_lr_rate: 0.1
packing: false
max_grad_norm: 0.2
max_length: 512
max_steps: -1
num_train_epochs: 10
output_dir: data/Qwen2.5-0.5B-SFT
overwrite_output_dir: true
per_device_eval_batch_size: 1
per_device_train_batch_size: 2
push_to_hub: true
report_to:
- wandb
save_strategy: epoch
save_total_limit: 1
seed: 42
use_liger_kernel: true
warmup_ratio: 0.03