will examples update the parameters of bert model?
on the examples, it loads bert-base model and do some tasks, the paper says that it will fix the parameters of bert and only update  the parameters of our tasks, but i find that it seems not fix parameters of bert? just load the model, and adds some layers to train
Could you please show the part of the paper where you have seen mentioned, I haven't found it.

Are you talking about this paragraph?

>In this section we evaluate how well BERT performs in the feature-based approach by generating ELMo-like pre-trained contextual representations on the CoNLL-2003 NER task. To do this, we use the same input representation as in Section 4.3, but use the activations from one or more layers with- out fine-tuning any parameters of BERT. These contextual embeddings are used as input to a randomly initialized two-layer 768-dimensional BiLSTM before the classification layer.<|||||>Closing this since there no activity. Feel free to re-open if needed.<|||||>i think it is asking whether we are fine-tuning the whole bert model or use bert outputs as a fixed feature for representing the sentences (like ELMO)