Comments (3)
yangapku
commented on May 22, 2024
我们整理一下哈
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ddNTP
commented on May 22, 2024
还有，我想问下，8卡（A100 80G）能复现flickr30k-cn和coco-cn中论文给的finetune的结果吗？比如通过调超参和梯度累加之类的方法。
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DtYXs
commented on May 22, 2024
您好，coco-cn的finetune脚本更新到了最新的代码中run_scripts/coco-cn_finetune_vit-b-16_rbt-base.sh，其中超参已经适配到8卡A100，启用了grad-checkpointing。准备好数据集后，您只需要将MASTER_ADDR修改为localhost应该就可以直接运行了，可以选择验证集上表现最好的ckpt测试，应该可以与论文中32卡的结果较为一致。
对于8卡A100复现flickr30k-cn的结果，目前有一组经验上的超参batchsize=400 lr=1e-5 max_epochs=16 warmup=20，可以大体接近32卡的结果，理论上通过调超参还可以进一步提升，供您参考，也欢迎您提供更好的超参配置。
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Related Issues (20)
- 使用RN50预训练模型和flick30k后得到的权重文件特别大 HOT 2
- text描述
- 为什么使用同样的词和图片得到的结果不一致？
- Downlodaded issue
- 关于ACC和R@5的问题 HOT 13
- LOSS:nan 微调时LOSS异常 HOT 12
- 无进行任何微调，直接用模型对总的数据集进行测试R@5值为50多，把总数据集切割为train、test和valid后直接测试R@5为10多
- 在finetune时报错KeyError: 'optimizer' HOT 1
- finetune时报错，且Traceback疑似被截断，无法定位出错线程 HOT 3
- 微调clip_cn_vit-l-14-336 报错 HOT 2
- 请问在线demo中的文搜图或图搜图应用，对返回结果的逻辑处理是怎么样的呢？我设置了返回50张，但是有的文本只返回了32张。请问你们是对结果进行了阈值过滤吗，阈值设置的多少呢？用于检索的数据有哪些呢？
- Delete
- 执行finetune流程时报错 HOT 1
- 请问demo用的base模型跟本项目给的CN-CLIP（ViT-B/16）是同一个模型吗？跟我本地的测试结果不太一样
- 请问怎么调用这个模型？怎么提供api服务？
- 文搜图的原理
- fb16速度比fb32要慢
- 请问分词器有没有c++版本的实现？ HOT 1
- 请问训练脚本会在当验证集上性能下降时停止训练吗，还是说只是会汇报下验证集上的性能但训练继续
- load_from_name 加入 flash-attn 支持
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