| This is a `microsoft/codebert-base-mlm` model, trained for 1,000,000 steps (with `batch_size=32`) on **Java** code from the `codeparrot/github-code-clean` dataset, on the masked-language-modeling task. | |
| It is intended to be used in CodeBERTScore: [https://github.com/neulab/code-bert-score](https://github.com/neulab/code-bert-score), but can be used for any other model or task. | |
| For more information, see: [https://github.com/neulab/code-bert-score](https://github.com/neulab/code-bert-score) | |
| ## Citation | |
| If you use this model for research, please cite: | |
| ``` | |
| @article{zhou2023codebertscore, | |
| url = {https://arxiv.org/abs/2302.05527}, | |
| author = {Zhou, Shuyan and Alon, Uri and Agarwal, Sumit and Neubig, Graham}, | |
| title = {CodeBERTScore: Evaluating Code Generation with Pretrained Models of Code}, | |
| publisher = {arXiv}, | |
| year = {2023}, | |
| } | |
| ``` |