adminstrateur/bert-sentiment-v2

Fine-tune of prajjwal1/bert-tiny

The following model is a Pytorch pre-trained model obtained from converting Tensorflow checkpoint found in the official Google BERT repository.

This is one of the smaller pre-trained BERT variants, together with bert-mini bert-small and bert-medium. They were introduced in the study Well-Read Students Learn Better: On the Importance of Pre-training Compact Models (arxiv), and ported to HF for the study Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics (arXiv). 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-tiny (L=2, H=128) Model Link

Original author : @prajjwal_1