| --- |
| base_model: huggingface/CodeBERTa-small-v1 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: training |
| results: [] |
| --- |
| |
| # training |
|
|
| This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on an [my a dataset curated from The Technical Debt Dataset](https://huggingface.co/datasets/davidgaofc/techdebt). |
|
|
| # dataset citation |
| Valentina Lenarduzzi, Nyyti Saarimäki, Davide Taibi. The Technical Debt Dataset. Proceedings for the 15th Conference on Predictive Models and Data Analytics in Software Engineering. Brazil. 2019. |
|
|
| ## Model description |
|
|
| Classifies cleaned diffs of code. |
| * 1: exhibits possible technical debt |
| * 0: is probably clean |
|
|
| ## Intended uses & limitations |
|
|
| Limited by many things probably, use with caution. Improvements in progress. |
|
|
| ## Training and evaluation data |
|
|
| ~95% accurate on the test split of dataset above |
| ~.94 F1 score on test split of dataset above. |
|
|
|
|
| ## Training procedure |
| One epoch of training done on the dataset above. |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 30 |
| - eval_batch_size: 30 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 1 |
|
|
| ### Framework versions |
|
|
| - Transformers 4.35.0 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
|
|
