| language: | |
| - hi | |
| - en | |
| tags: | |
| - hi | |
| - en | |
| - codemix | |
| datasets: | |
| - SAIL 2017 | |
| # Model name | |
| ## Model description | |
| I took a bert-base-multilingual-cased model from huggingface and finetuned it on SAIL 2017 dataset. | |
| ## Intended uses & limitations | |
| #### How to use | |
| ```python | |
| # You can include sample code which will be formatted | |
| #Coming soon! | |
| ``` | |
| #### Limitations and bias | |
| Provide examples of latent issues and potential remediations. | |
| ## Training data | |
| I trained on the SAIL 2017 dataset [link](http://amitavadas.com/SAIL/Data/SAIL_2017.zip) on this [pretrained model](https://huggingface.co/bert-base-multilingual-cased). | |
| ## Training procedure | |
| No preprocessing. | |
| ## Eval results | |
| ### BibTeX entry and citation info | |
| ```bibtex | |
| @inproceedings{khanuja-etal-2020-gluecos, | |
| title = "{GLUEC}o{S}: An Evaluation Benchmark for Code-Switched {NLP}", | |
| author = "Khanuja, Simran and | |
| Dandapat, Sandipan and | |
| Srinivasan, Anirudh and | |
| Sitaram, Sunayana and | |
| Choudhury, Monojit", | |
| booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics", | |
| month = jul, | |
| year = "2020", | |
| address = "Online", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://www.aclweb.org/anthology/2020.acl-main.329", | |
| pages = "3575--3585" | |
| } | |
| ``` | |