| | --- |
| | language: en |
| | thumbnail: https://huggingface.co/front/thumbnails/microsoft.png |
| | tags: |
| | - text-classification |
| | license: mit |
| | --- |
| | |
| | # AutoDisProxyT-QNLI for Distilling Massive Neural Networks |
| |
|
| | AutoDisProxyT is a distilled task-agnostic transformer model that leverages task transfer for learning a small universal model that can be applied to arbitrary tasks and languages as outlined in the paper [Few-shot Task-agnostic Neural Architecture Search for |
| | Distilling Large Language Models](https://proceedings.neurips.cc/paper_files/paper/2022/file/b7c12689a89e98a61bcaa65285a41b7c-Paper-Conference.pdf). |
| | |
| | This AutoDisProxyT checkpoint with **7** layers, **160** hidden size, **10** attention heads corresponds to **6.88 million** parameters and **0.27G** FLOPs. |
| | |
| | The following table shows the results on GLUE dev set. |
| | |
| | | Models | #Params (M) | #FLOPs (G) | MNLI | QNLI | QQP | RTE | SST-2 | MRPC | CoLA | Avg | |
| | |----------------|--------|---------|------|------|------|------|------|------|--------|-------| |
| | | BERT | 109 | 11.2 | 84.5 | 91.7 | 91.3 | 68.6 | 93.2 | 87.3 | 53.5 | 82.2 | |
| | | BERT<sub>SMALL</sub> | 66 | 5.66 | 81.8 | 89.8 | 90.6 | 67.9 | 91.2 | 84.9 | 53.5 | 80.0 | |
| | | TruncatedBERT | 66 | 5.66 | 81.2 | 87.9 | 90.4 | 65.5 | 90.8 | 82.7 | 41.4 | 77.1 | |
| | | DistilBERT | 66 | 5.66 | 82.2 | 89.2 | 88.5 | 59.9 | 91.3 | 87.5 | 51.3 | 78.6 | |
| | | TinyBERT | 66 | 5.66 | 83.5 | 90.5 | 90.6 | 72.2 | 91.6 | 88.4 | 42.8 | 79.9 | |
| | | MiniLM | 66 | 5.66 | 84.0 | 91.0 | 91.0 | 71.5 | 92.0 | 88.4 | 49.2 | 81.0 | |
| | | AutoTinyBERT-KD-S1 | 30.0 | 1.69 | 82.3 | 89.7 | 89.9 | 71.1 | 91.4 | 88.5 | 47.3 | 80.0 | |
| | | DynaBERT | 37.7 | 1.81 | 82.3 | 88.5 | 90.4 | 63.2 | 92.0 | 81.4 | 76.4 | 43.7 | |
| | | NAS-BERT<sub>10</sub>| 10.0 | 2.30 | 76.4 | 86.3 | 88.5 | 66.6 | 88.6 | 79.1 | 34.0 | 74.2 | |
| | | AutoTinyBERT-KD-S4 | 66 | 5.66 | 76.0 | 85.5 | 86.9 | 64.9 | 86.8 | 81.4 | 20.4 | 71.7 | |
| | | NAS-BERT<sub>5</sub> | 66 | 5.66 | 74.4 | 84.9 | 85.8 | 66.6 | 87.3 | 79.6 | 19.8 | 71.2 | |
| | | **AutoDisProxyT** | 6.88 | 0.27 | 79.0 | 86.4 | 89.1 | 64.3 | 85.9 | 78.5 | 24.8 | 72.6 | |
| | |
| | Tested with `torch 1.6.0` |
| | |
| | If you use this checkpoint in your work, please cite: |
| | |
| | ``` latex |
| | @article{xu2022autodistil, |
| | title={AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models}, |
| | author={Xu, Dongkuan and Mukherjee, Subhabrata and Liu, Xiaodong and Dey, Debadeepta and Wang, Wenhui and Zhang, Xiang and Awadallah, Ahmed Hassan and Gao, Jianfeng}, |
| | journal={arXiv preprint arXiv:2201.12507}, |
| | year={2022} |
| | } |
| | ``` |
| | |
