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--- |
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language: |
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- code |
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metrics: |
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- perplexity |
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library_name: transformers |
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pipeline_tag: fill-mask |
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tags: |
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- MLM |
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--- |
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# Model Card for Model ID |
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A BERT-like model pre-trained on Java buggy code. |
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## Model Details |
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### Model Description |
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A BERT-like model pre-trained on Java buggy code. |
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- **Developed by:** André Nascimento |
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- **Shared by:** Hugging Face |
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- **Model type:** Fill-Mask |
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- **Language(s) (NLP):** Java (EN) |
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- **License:** [More Information Needed] |
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- **Finetuned from model:** [BERT Base Uncased](https://huggingface.co/bert-base-cased) |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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### Direct Use |
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Fill-Mask. |
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### Downstream Use [optional] |
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The model can be used for other tasks, like Text Classification. |
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### Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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[More Information Needed] |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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[More Information Needed] |
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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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```python |
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from transformers import pipeline |
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unmasker = pipeline('fill-mask', model='bert-java-bfp_single') |
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unmasker(java_code) # Replace with Java code; Use '[MASK]' to mask tokens/words in the code. |
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``` |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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The model was trained on 236040 Java methods, containing the code before and after the bug fix was applied. The whole dataset was built from [Extracted Bug-Fix Pairs (BFP)](https://sites.google.com/view/learning-fixes/data#h.p_RNvM6OfOYBMI), extracting single file/single method commits, and keeping only method with less than 512 tokens. An 80/20 train/validation split was applied afterwards. |
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### Training Procedure |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Preprocessing [optional] |
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Remove comments and replace consecutive whitespace characters by a single space. |
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#### Training Hyperparameters |
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- **Training regime:** fp16 mixed precision <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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#### Speeds, Sizes, Times [optional] |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
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[More Information Needed] |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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The model was evaluated on 59024 Java methods, from the 20% split of the dataset mentioned in [Training Data](#training-data) |
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[More Information Needed] |
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#### Factors |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
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[More Information Needed] |
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#### Metrics |
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<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
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Perplexity |
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### Results |
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1.73 |
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#### Summary |
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## Model Examination [optional] |
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<!-- Relevant interpretability work for the model goes here --> |
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[More Information Needed] |
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## Environmental Impact |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
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- **Hardware Type:** [More Information Needed] |
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- **Hours used:** [More Information Needed] |
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- **Cloud Provider:** [More Information Needed] |
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- **Compute Region:** [More Information Needed] |
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- **Carbon Emitted:** [More Information Needed] |
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## Technical Specifications [optional] |
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### Model Architecture and Objective |
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[More Information Needed] |
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### Compute Infrastructure |
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[More Information Needed] |
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#### Hardware |
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[More Information Needed] |
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#### Software |
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[More Information Needed] |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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## Glossary [optional] |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> |
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[More Information Needed] |
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## More Information [optional] |
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[More Information Needed] |
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## Model Card Authors [optional] |
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[More Information Needed] |
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## Model Card Contact |
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[More Information Needed] |
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