NamCyan
/

starcoder2-3b-technical-debt-code-tesoro

@@ -1,199 +1,77 @@
 ---
 library_name: transformers
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 ---
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 ---
 library_name: transformers
+datasets:
+- NamCyan/tesoro-code
+base_model:
+- bigcode/starcoder2-3b
 ---
+# Improving the detection of technical debt in Java source code with an enriched dataset
 ## Model Details
 ### Model Description
+This model is the part of Tesoro project, used for detecting technical debt in source code. More information can be found at [Tesoro HomePage](https://github.com/NamCyan/tesoro.git).
+- **Developed by:** [Nam Hai Le](https://github.com/NamCyan)
+- **Model type:** Encoder-Decoder-based PLMs
+- **Language(s):** Java
+- **Finetuned from model:** [StarCoder2](https://huggingface.co/bigcode/starcoder2-3b)
+### Model Sources
+- **Repository:** [Tesoro](https://github.com/NamCyan/tesoro.git)
+- **Paper:** [To be update]
 ## How to Get Started with the Model
 Use the code below to get started with the model.
+```python
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained("NamCyan/starcoder2-3b-technical-debt-code-tesoro")
+model = AutoModelForSequenceClassification.from_pretrained("NamCyan/starcoder2-3b-technical-debt-code-tesoro")
+```
+## Training Details
+- Training Data: The model is finetuned using [tesoro-code](https://huggingface.co/datasets/NamCyan/tesoro-code)
+- Infrastructure: Training process is conducted on two NVIDIA A100 GPUs with 80GB of VRAM.
+## Leaderboard
+| Model | Model size  | EM            | F1              |
+|:-------------|:-----------|:------------------|:------------------|
+| **Encoder-based PLMs** |
+| [CodeBERT](https://huggingface.co/microsoft/codebert-base)     | 125M       | 38.28             | 43.47             |
+| [UniXCoder](https://huggingface.co/microsoft/unixcoder-base)    | 125M       | 38.12             | 42.58             |
+| [GraphCodeBERT](https://huggingface.co/microsoft/graphcodebert-base)| 125M       | *39.38*          | *44.21*           |
+| [RoBERTa](https://huggingface.co/FacebookAI/roberta-base)      | 125M       | 35.37             | 38.22             |
+| [ALBERT](https://huggingface.co/albert/albert-base-v2)       | 11.8M      | 39.32             | 41.99             |
+| **Encoder-Decoder-based PLMs** |
+| [PLBART](https://huggingface.co/uclanlp/plbart-base)       | 140M       | 36.85             | 39.90             |
+| [Codet5](https://huggingface.co/Salesforce/codet5-base)       | 220M       | 32.66             | 35.41             |
+| [CodeT5+](https://huggingface.co/Salesforce/codet5p-220m)      | 220M       | 37.91             | 41.96             |
+| **Decoder-based PLMs (LLMs)** |
+| [TinyLlama](https://huggingface.co/TinyLlama/TinyLlama_v1.1_math_code)    | 1.03B      | 37.05             | 40.05             |
+| [DeepSeek-Coder](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) | 1.28B    | **42.52**         | **46.19**         |
+| [OpenCodeInterpreter](https://huggingface.co/m-a-p/OpenCodeInterpreter-DS-1.3B)       | 1.35B             | 38.16             | 41.76             |
+| [phi-2](https://huggingface.co/microsoft/phi-2)        | 2.78B      | 37.92             | 41.57             |
+| [starcoder2](https://huggingface.co/bigcode/starcoder2-3b)   | 3.03B      | 35.37             | 41.77             |
+| [CodeLlama](https://huggingface.co/codellama/CodeLlama-7b-hf)    | 6.74B      | 34.14             | 38.16             |
+| [Magicoder](https://huggingface.co/ise-uiuc/Magicoder-S-DS-6.7B)    | 6.74B      | 39.14             | 42.49             |
+## Citing us
+```bibtex
+@article{nam2024tesoro,
+  title={Improving the detection of technical debt in Java source code with an enriched dataset},
+  author={Hai, Nam Le and Bui, Anh M. T. Bui and Nguyen, Phuong T. and Ruscio, Davide Di and Kazman, Rick},
+  journal={},
+  year={2024}
+}
+```