# DynaBERT: Dynamic BERT with Adaptive Width and Depth* DynaBERT can flexibly adjust the size and latency by selecting adaptive width and depth, and the subnetworks of it have competitive performances as other similar-sized compressed models.The training process of DynaBERT includes first training a width-adaptive BERT and then allowing both adaptive width and depth using knowledge distillation. * This code is modified based on the repository developed by Hugging Face: [Transformers v2.1.1](https://github.com/huggingface/transformers/tree/v2.1.1)* The results in the paper are produced by using single V100 GPU.
