| thumbnail: https://raw.githubusercontent.com/JetRunner/BERT-of-Theseus/master/bert-of-theseus.png | |
| datasets: | |
| - multi_nli | |
| # BERT-of-Theseus | |
| See our paper ["BERT-of-Theseus: Compressing BERT by Progressive Module Replacing"](http://arxiv.org/abs/2002.02925). | |
| BERT-of-Theseus is a new compressed BERT by progressively replacing the components of the original BERT. | |
|  | |
| ## Load Pretrained Model on MNLI | |
| We provide a 6-layer pretrained model on MNLI as a general-purpose model, which can transfer to other sentence classification tasks, outperforming DistillBERT (with the same 6-layer structure) on six tasks of GLUE (dev set). | |
| | Method | MNLI | MRPC | QNLI | QQP | RTE | SST-2 | STS-B | | |
| |-----------------|------|------|------|------|------|-------|-------| | |
| | BERT-base | 83.5 | 89.5 | 91.2 | 89.8 | 71.1 | 91.5 | 88.9 | | |
| | DistillBERT | 79.0 | 87.5 | 85.3 | 84.9 | 59.9 | 90.7 | 81.2 | | |
| | BERT-of-Theseus | 82.1 | 87.5 | 88.8 | 88.8 | 70.1 | 91.8 | 87.8 | | |
| Please Note: this checkpoint is for [Intermediate-Task Transfer Learning](https://arxiv.org/abs/2005.00628) so it does not include the classification head for MNLI! Please fine-tune it before use (like DistilBERT). | |