---
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