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Describe the bug Lora 训练 QwQ-32B,merge LoRA 后,tokenizer.json 变大,推理生成乱码
Your hardware and system info 昇腾 910B4 * 8 Driver version: 24.1.0.3 CANN version: 8.1.RC1 torch 2.5.1 torch-npu 2.5.1.dev20250228 deepspeed 0.14.5 ms_swift 3.2.0
SFT 命令: nohup swift sft --model $MODEL_PATH --sequence_parallel_size $SEQUENCE_PARALLEL_SIZE --torch_dtype 'bfloat16' --model_type 'qwq' --template 'qwq' --init_weights 'True' --dataset $DATASET --dataloader_num_workers $NPROC_PER_NODE --torch_dtype 'bfloat16' --num_train_epochs 8 --gradient_checkpointing --per_device_train_batch_size 1 --per_device_eval_batch_size 1 --gradient_accumulation_steps 1 --learning_rate 1e-4 --train_type 'lora' --lora_rank 64 --lora_alpha 128 --target_regex ".*.(q_proj|k_proj|v_proj|o_proj)" --lora_dtype 'bfloat16' --init_weights true --eval_steps 10000 --save_steps 500 --save_total_limit 2 --split_dataset_ratio 0 --logging_steps 10 --max_length 6144 --truncation_strategy 'right' --output_dir $CHECKPOINT_PATH --logging_dir $LOG_DIR --report_to 'tensorboard' --output_dir $CHECKPOINT_PATH --warmup_ratio 0.01 --max_grad_norm 1.0 --deepspeed "$BASE_DIR/conf/zero3_offload.json" $RESUME_OPTS >> $LOG_FILE 2>&1 &
Export 命令: swift export --adapters $CHECKPOINT_PATH --merge_lora true --device_map 'cpu' --output_dir "$OUTPUT_PATH" \
The text was updated successfully, but these errors were encountered:
这个估计是tokenizers版本的问题,swift直接使用tokenizer.save_pretrained接口来存储
Sorry, something went wrong.
transformers 4.44 后,依赖的 tokenizers 会把 merges 写成二维数组导致的。
使用 swift-3.0.3 merge 就没有问题没有问题 (swift 3.0.3 以后的版本,trl >=0.13 -> transformers >=4.46)
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Describe the bug
Lora 训练 QwQ-32B,merge LoRA 后,tokenizer.json 变大,推理生成乱码
Your hardware and system info
昇腾 910B4 * 8
Driver version: 24.1.0.3
CANN version: 8.1.RC1
torch 2.5.1
torch-npu 2.5.1.dev20250228
deepspeed 0.14.5
ms_swift 3.2.0
SFT 命令:
nohup swift sft
--model $MODEL_PATH
--sequence_parallel_size $SEQUENCE_PARALLEL_SIZE
--torch_dtype 'bfloat16'
--model_type 'qwq'
--template 'qwq'
--init_weights 'True'
--dataset $DATASET
--dataloader_num_workers $NPROC_PER_NODE
--torch_dtype 'bfloat16'
--num_train_epochs 8
--gradient_checkpointing
--per_device_train_batch_size 1
--per_device_eval_batch_size 1
--gradient_accumulation_steps 1
--learning_rate 1e-4
--train_type 'lora'
--lora_rank 64
--lora_alpha 128
--target_regex ".*.(q_proj|k_proj|v_proj|o_proj)"
--lora_dtype 'bfloat16'
--init_weights true
--eval_steps 10000
--save_steps 500
--save_total_limit 2
--split_dataset_ratio 0
--logging_steps 10
--max_length 6144
--truncation_strategy 'right'
--output_dir $CHECKPOINT_PATH
--logging_dir $LOG_DIR
--report_to 'tensorboard'
--output_dir $CHECKPOINT_PATH
--warmup_ratio 0.01
--max_grad_norm 1.0
--deepspeed "$BASE_DIR/conf/zero3_offload.json"
$RESUME_OPTS
>> $LOG_FILE 2>&1 &
Export 命令:
swift export
--adapters $CHECKPOINT_PATH
--merge_lora true
--device_map 'cpu'
--output_dir "$OUTPUT_PATH" \
The text was updated successfully, but these errors were encountered: