在Flickr30k-CN数据的fintune实验上,无法复现论文,特别是valid上表现,低于10%
训练配置:
## Number of GPUs per GPU worker
GPUS_PER_NODE=8
## Number of GPU workers, for single-worker training, please set to 1
WORKER_CNT=1
## The ip address of the rank-0 worker, for single-worker training, please set to localhost
export MASTER_ADDR=127.0.0.1
## The port for communication
export MASTER_PORT=8514
## The rank of this worker, should be in {0, ..., WORKER_CNT-1}, for single-worker training, please set to 0
export RANK=0
context_length=52
warmup=100
batch_size=512
valid_batch_size=512
accum_freq=2
lr=5e-4
wd=0.001
max_epochs=30 # or you can alternatively specify --max-steps
valid_step_interval=150
valid_epoch_interval=1
vision_model=ViT-B-16
text_model=RoBERTa-wwm-ext-base-chinese
## mask_ratio=0.5 # use flip: set mask ratio
use_augment="--use-augment"
use_augment=""
1条答案
按热度按时间falq053o1#
\n\n您好,您可以参考我们在技术报告中给出的超参数配置。大多数finetune实验都是在32卡上进行的。根据您的情况,您的finetune实验应该是在单机8卡上进行的。您可以尝试使用经过单机8卡验证的COCO-CN脚本默认参数来进行COCO-CN finetune实验。