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LLaMA-Factory-Mirror
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Merge pull request #434 from niuba/main 

add last_checkpoint support
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hoshi-hiyouga 2023-08-18 01:38:31 +08:00 committed by GitHub
parent d125218cde 7252903245
commit 7926432d27
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1 changed files with 10 additions and 1 deletions
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11
src/llmtuner/tuner/sft/workflow.py
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@ -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()