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Open Source Model Profile · neulab

codebert-javascript

codebert-javascript is a neulab RoBERTa fill-mask model for JavaScript code. Its model card documents continued training from microsoft/codebert-base-mlm.

Publisher
neulab
Task
fill-mask
Model type
roberta
License
Unknown
Library
transformers
Publication status
Accepted · not indexed

Model overview

codebert-javascript is published by neulab as a fill-mask model. The captured configuration identifies RobertaForMaskedLM with model type roberta. According to the model card, it is a microsoft/codebert-base-mlm model trained on JavaScript code from codeparrot/github-code-clean.

Recorded capabilities

JavaScript MLM training

According to the model card, the model was trained for 1,000,000 steps with batch size 32 on JavaScript code from codeparrot/github-code-clean.

CodeBERTScore purpose

According to the model card, it is intended for CodeBERTScore evaluation of code generation, with citation and repository pointers.

Use cases in the source record

  • JavaScript code evaluation inside CodeBERTScore, the card's stated intended use.
  • General fill-mask modeling over JavaScript code for research tasks beyond CodeBERTScore.

Limitations and unknowns

  • No parameter count was extracted from this record.
  • No license value was extracted from this record.
  • No evaluation results were extracted from this record.
  • No context-window value was extracted from this record.
  • Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: neulab/codebert-javascript

Captured: Unknown. Processed: 2026-09-07T19:34:53.249336+00:00.

This is a microsoft/codebert-base-mlm model, trained for 1,000,000 steps (with batch_size=32 ) on JavaScript 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 , but can be used for any other model or task. For more information, see: 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: Evalua…

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