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The score code of FastBERT (ACL2020)

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line 234: ```python self._self_distillation( sentences_train, batch_size, learning_rate, epochs_num, warmup, report_steps, model_saving_pathm, sentences_dev, labels_dev, dev_speed, verbose ) ``` `model_saving_pathm`应该是`model_saving_path`吧

请问如果我是多标签任务,在每个维度独立做二分类 1.可以直接用KL散度做蒸馏loss吗 2.可以用类别维度的熵表示不确定性吗

Hi, I have a very rookie question. How can I calculate the FLOPs of BERT model? I tried to use thop, ``` macs, params = profile(model, inputs=(input, ), custom_ops={YourModule: count_your_model})...

Hi, I found in MultiHeadedAttention, thop only count the FLOPS of linear layer, missing the attention operation.

我好想没有找到批量预测的代码块,请问在哪里啊

Would you clarify what the Weibo dataset (one of the benchmarked task in the paper) is or provide a copy in this repo?

这344行是个空行,有啥问题吗

Could you can provide source code early, we want to try and follow your work, Thanks

作者大大您好,首先非常感谢您的开源精神和杰出的工作,我有一点疑惑向来咨询一下大大。就是我采用speed=0.5,batch_size=64,预训练加载的是我在其他数据集上已经重新委托过的BERT模型,但是运行fastbert后最终的结果准确度却下降了20%,如下图所示 ![屏幕截图 2023-04-22 182241](https://user-images.githubusercontent.com/125568740/233783444-26a1dd3c-dd78-402d-91c1-3cc87965d7c6.png) ![屏幕截图 2023-04-22 181936](https://user-images.githubusercontent.com/125568740/233783446-4bcba447-326c-4bcf-a127-378a38071e85.png) 我有些疑惑,按道理来说不应该出现这样的问题啊,还是说作者大大的模型只对readme中提到的那几个模型有用,在其他数据集上微调的BERT模型不可以使用本文的程序吗?请作者大大解答一下,非常感谢