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--- |
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base_model: huggingface/CodeBERTa-small-v1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: training |
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results: [] |
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--- |
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# training |
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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). |
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# dataset citation |
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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. |
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## Model description |
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Classifies cleaned diffs of code. |
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* 1: exhibits possible technical debt |
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* 0: is probably clean |
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## Intended uses & limitations |
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Limited by many things probably, use with caution. Improvements in progress. |
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## Training and evaluation data |
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~95% accurate on the test split of dataset above |
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~.94 F1 score on test split of dataset above. |
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## Training procedure |
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One epoch of training done on the dataset above. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 30 |
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- eval_batch_size: 30 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1 |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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