diff --git a/src/llmtuner/tuner/sft/workflow.py b/src/llmtuner/tuner/sft/workflow.py
index b28fa1dc..ebb16edd 100644
--- a/src/llmtuner/tuner/sft/workflow.py
+++ b/src/llmtuner/tuner/sft/workflow.py
@@ -1,4 +1,5 @@
 # Inspired by: https://github.com/huggingface/transformers/blob/v4.29.2/examples/pytorch/summarization/run_summarization.py
+import os
 
 from typing import TYPE_CHECKING, Optional, List
 from transformers import DataCollatorForSeq2Seq
@@ -10,11 +11,14 @@ from llmtuner.extras.ploting import plot_loss
 from llmtuner.tuner.core import load_model_and_tokenizer
 from llmtuner.tuner.sft.metric import ComputeMetrics
 from llmtuner.tuner.sft.trainer import Seq2SeqPeftTrainer
+from transformers.trainer_utils import get_last_checkpoint
+from llmtuner.extras.logging import reset_logging, get_logger
 
 if TYPE_CHECKING:
     from transformers import Seq2SeqTrainingArguments, TrainerCallback
     from llmtuner.hparams import ModelArguments, DataArguments, FinetuningArguments, GeneratingArguments
 
+logger = get_logger(__name__)
 
 def run_sft(
     model_args: "ModelArguments",
@@ -58,7 +62,12 @@ def run_sft(
 
     # Training
     if training_args.do_train:
-        train_result = trainer.train()
+        checkpoint = None
+        if training_args.resume_from_checkpoint is not None:
+            checkpoint = training_args.resume_from_checkpoint
+        elif last_checkpoint is not None:
+            checkpoint = last_checkpoint
+        train_result = trainer.train(resume_from_checkpoint=checkpoint)
         trainer.log_metrics("train", train_result.metrics)
         trainer.save_metrics("train", train_result.metrics)
         trainer.save_state()