readme: ---
  language: 
    - en
  
  license:
  - mit  
    
  tags:
  - BERT
  - MNLI
  - NLI
  - transformer
  - pre-training
  
  ---
  
  The following model is a Pytorch pre-trained model obtained from converting Tensorflow checkpoint found in the [official Google BERT repository](https://github.com/google-research/bert). 
  
  This is one of the smaller pre-trained BERT variants, together with [bert-tiny](https://huggingface.co/prajjwal1/bert-tiny), [bert-mini](https://huggingface.co/prajjwal1/bert-mini) and [bert-small](https://huggingface.co/prajjwal1/bert-small). They were introduced in the study `Well-Read Students Learn Better: On the Importance of Pre-training Compact Models` ([arxiv](https://arxiv.org/abs/1908.08962)), and ported to HF for the study `Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics` ([arXiv](https://arxiv.org/abs/2110.01518)). These models are supposed to be trained on a downstream task.
  
  If you use the model, please consider citing both the papers:
  ```
  @misc{bhargava2021generalization,
        title={Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics}, 
        author={Prajjwal Bhargava and Aleksandr Drozd and Anna Rogers},
        year={2021},
        eprint={2110.01518},
        archivePrefix={arXiv},
        primaryClass={cs.CL}
  }
  
  @article{DBLP:journals/corr/abs-1908-08962,
    author    = {Iulia Turc and
                 Ming{-}Wei Chang and
                 Kenton Lee and
                 Kristina Toutanova},
    title     = {Well-Read Students Learn Better: The Impact of Student Initialization
                 on Knowledge Distillation},
    journal   = {CoRR},
    volume    = {abs/1908.08962},
    year      = {2019},
    url       = {http://arxiv.org/abs/1908.08962},
    eprinttype = {arXiv},
    eprint    = {1908.08962},
    timestamp = {Thu, 29 Aug 2019 16:32:34 +0200},
    biburl    = {https://dblp.org/rec/journals/corr/abs-1908-08962.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
  }
  
  ```
  Config of this model:
  - `prajjwal1/bert-medium` (L=8, H=512) [Model Link](https://huggingface.co/prajjwal1/bert-medium)
  
  
  
  Other models to check out:
  - `prajjwal1/bert-tiny` (L=2, H=128) [Model Link](https://huggingface.co/prajjwal1/bert-tiny)
  - `prajjwal1/bert-mini` (L=4, H=256) [Model Link](https://huggingface.co/prajjwal1/bert-mini)
  - `prajjwal1/bert-small` (L=4, H=512) [Model Link](https://huggingface.co/prajjwal1/bert-small)
  
  Original Implementation and more info can be found in [this Github repository](https://github.com/prajjwal1/generalize_lm_nli).
  
  Twitter: [@prajjwal_1](https://twitter.com/prajjwal_1)
  