PaddlePaddle
P-tuning用自己准备的二分类数据做测试时，预测的概率很小，正负概率和远小于1
你好，
在做p-tuning模型，采用的是自己的二分类数据集，训练后进行predict的预测，预测后的概率总是很小，正负概率和远小于1。想请教一下这是什么问题导致的。以及自测数据在p-tuning中有没有参考代码。需要做什么另外的处理吗。谢谢
您好，P-Tuning 预测空间是在整个词表规模进行，具体到某个 Lable 上绝对概率数值很小符合预期，概率值的相对大小更具有参考意义。自测数据在 p-tuning 中有没有参考代码 这个具体需求或者问题可以再明确下吗？没太理解您的需求。
假设做新闻分类任务，给定分类文本: 姚明狂砍 38 分，这是一条[MASK][MASK]新闻，Label 是 体育, 预测出 Label 为 体育 的概率 = P(体) * P(育)
This issue is stale because it has been open for 60 days with no activity. 当前issue 60天内无活动，被标记为stale。
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This issue is stale because it has been open for 60 days with no activity. 当前issue 60天内无活动，被标记为stale。
This issue is stale because it has been open for 60 days with no activity. 当前issue 60天内无活动，被标记为stale。
This issue is stale because it has been open for 60 days with no activity. 当前issue 60天内无活动，被标记为stale。
This issue is stale because it has been open for 60 days with no activity. 当前issue 60天内无活动，被标记为stale。
This issue is stale because it has been open for 60 days with no activity. 当前issue 60天内无活动，被标记为stale。
This issue is stale because it has been open for 60 days with no activity. 当前issue 60天内无活动，被标记为stale。
This issue is stale because it has been open for 60 days with no activity. 当前issue 60天内无活动，被标记为stale。
This issue is stale because it has been open for 60 days with no activity. 当前issue 60天内无活动，被标记为stale。
This issue is stale because it has been open for 60 days with no activity. 当前issue 60天内无活动，被标记为stale。