language:
- code
metrics:
- perplexity
library_name: transformers
pipeline_tag: fill-mask
tags:
- MLM
Model Card for Model ID
A BERT-like model pre-trained on Java buggy code.
Model Details
Model Description
A BERT-like model pre-trained on Java buggy code.
- Developed by: André Nascimento
- Shared by: Hugging Face
- Model type: Fill-Mask
- Language(s) (NLP): Java (EN)
- License: [More Information Needed]
- Finetuned from model: BERT Base Uncased
Uses
Direct Use
Fill-Mask.
Downstream Use [optional]
The model can be used for other tasks, like Text Classification.
Out-of-Scope Use
[More Information Needed]
Bias, Risks, and Limitations
[More Information Needed]
Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
from transformers import pipeline
unmasker = pipeline('fill-mask', model='bert-java-bfp_single')
unmasker(java_code) # Replace with Java code; Use '[MASK]' to mask tokens/words in the code.
[More Information Needed]
Training Details
Training Data
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), extracting single file/single method commits, and keeping only method with less than 512 tokens. An 80/20 train/validation split was applied afterwards.
Training Procedure
Preprocessing [optional]
Remove comments and replace consecutive whitespace characters by a single space.
Training Hyperparameters
- Training regime: fp16 mixed precision
Speeds, Sizes, Times [optional]
[More Information Needed]
Evaluation
Testing Data, Factors & Metrics
Testing Data
The model was evaluated on 59024 Java methods, from the 20% split of the dataset mentioned in Training Data
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Factors
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Metrics
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Results
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Summary
Model Examination [optional]
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: [More Information Needed]
- Hours used: [More Information Needed]
- Cloud Provider: [More Information Needed]
- Compute Region: [More Information Needed]
- Carbon Emitted: [More Information Needed]
Technical Specifications [optional]
Model Architecture and Objective
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Compute Infrastructure
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Hardware
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Software
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Citation [optional]
BibTeX:
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APA:
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Glossary [optional]
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More Information [optional]
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Model Card Authors [optional]
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Model Card Contact
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