Comments (5)
感谢您的关注。有两点需要check一下。
一是特征的获取,下载完X-101-features.tgz,使用feats_process处理,确保这一步没问题。
二是语言模型的预训练,我微调之后,test_score为57%多点,val_score为58%多点。
这两步确认以后再跑RSTNet。
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你好,我也有遇到了同样的问题,进入RL之后性能急剧下降,cider也差不多是0.009,并且一个epoch的时间从几十分钟到了七八小时。在此之前,我check了以上两点,不知是否还有其他一些需要注意的问题?
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我用了作者所提供的模型第二步预训练也没有达到这个结果test_score为57%多点,val_score为58%多点。
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我用了作者所提供的模型第二步预训练也没有达到这个结果test_score为57%多点,val_score为58%多点。
请问,你解决这个问题了吗
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我把rstnet训练过程的tensorboard文件上传到tensorboard_logs文件夹中了,大家可以在训练过程中可视化对照一下,check一下是哪个阶段出现的问题。
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Related Issues (20)
- vocab.pkl HOT 1
- visualness HOT 1
- Question about the position encoding HOT 2
- online特征提取 HOT 6
- Cannot download the image_info_test2014.json HOT 2
- No such file or directory: 'vocab_language/vocab_bert_language.pkl' HOT 1
- 关于 online test 代码 HOT 2
- TypeError: 'generator' object is not callable HOT 2
- question about warning HOT 3
- online test 提交 HOT 4
- Some question about custom dataset HOT 1
- 请问用您的environment.yml创建conda环境时总是报各种依赖冲突,请问这种情况该如何解决呢?感谢 HOT 1
- 训练transformer时assert language_model_path is not None HOT 2
- 关于X152_grid_feature文件 HOT 5
- 关于supplementary material HOT 2
- 关于ResNext152数据集和spice指标 HOT 3
- Run for Custom dataset HOT 1
- 计算机配置 HOT 1
- Some question about the Adaptive-Attention (AA) module HOT 3
- questions about bert_model input
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