# test_env: 4 * H20
# fa2: 4 * 43GiB; 35.5s/it
# fa3: 4 * 43GiB; 32.4s/it
# https://github.com/Dao-AILab/flash-attention/tree/main#flashattention-3-beta-release
# pip install "transformers==4.53.*"

PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
NPROC_PER_NODE=4 \
CUDA_VISIBLE_DEVICES=0,1,2,3 \
swift sft \
    --model Qwen/Qwen2.5-7B \
    --train_type full \
    --dataset 'AI-ModelScope/LongAlpaca-12k' \
    --attn_impl flash_attention_3 \
    --num_train_epochs 3 \
    --split_dataset_ratio 0.01 \
    --torch_dtype bfloat16 \
    --per_device_train_batch_size 1 \
    --per_device_eval_batch_size 1 \
    --learning_rate 1e-5 \
    --gradient_accumulation_steps 4 \
    --packing true \
    --eval_steps 200 \
    --save_steps 200 \
    --logging_steps 5 \
    --max_length 16384 \
    --warmup_ratio 0.05 \
    --dataloader_num_workers 8 \
    --dataset_num_proc 8 \
    --save_total_limit 2 \
    --save_only_model true \
    --output_dir output/Qwen2.5-7B \
    --deepspeed zero3 \
    --use_liger_kernel true
