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---
datasets:
- bigcode/commitpackft
language:
- en
base_model:
- Qwen/Qwen2.5-Coder-1.5B-Instruct
license: apache-2.0
---
# Hi, Iโ€™m Seniru Epasinghe ๐Ÿ‘‹
Iโ€™m an AI undergraduate and an AI enthusiast, working on machine learning projects and open-source contributions.
I enjoy exploring AI pipelines, natural language processing, and building tools that make development easier.
---
## ๐ŸŒ Connect with me
[![Hugging Face](https://img.shields.io/badge/Hugging%20Face-seniruk-orange?logo=huggingface&logoColor=white)](https://huggingface.co/seniruk)   
[![Medium](https://img.shields.io/badge/Medium-seniruk_epasinghe-black?logo=medium&logoColor=white)](https://medium.com/@senirukepasinghe)   
[![LinkedIn](https://img.shields.io/badge/LinkedIn-seniru_epasinghe-blue?logo=linkedin&logoColor=white)](https://www.linkedin.com/in/seniru-epasinghe-b34b86232/)   
[![GitHub](https://img.shields.io/badge/GitHub-seth2k2-181717?logo=github&logoColor=white)](https://github.com/seth2k2)
---
- **Developed by:** seniruk
- **License:** apache-2.0
- **Finetuned from model :** unsloth/Qwen2.5-Coder-1.5B-Instruct
This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
---
base_model: unsloth/Qwen2.5-Coder-1.5B-Instruct
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- trl
license: apache-2.0
language:
- en
---
---
datasets:
- bigcode/commitpackft
---
# Purpose
Used for generating high quality commit messages for a given git difference
### Model Description
Generated by fine tuning Qwen2.5-Coder-1.5B-Instruct on bigcode/commitpackft dataset for 2 epochs
Trained on a total of 277 Languages
Achieved a final training loss in the range of 1- 1.7 (due to data set not containing equal data rows for each language)
For common languages(python, java ,javascripts,c etc) loss went for a minimum of 1.0335
## Environmental Impact
- **Hardware Type:** geforce RTX 4060 TI - 16GB]
- **Hours used:** 10 Hours
- **Cloud Provider:** local
### Results
![Logo](./image1.png)
![Logo](./image2.png)
### Inference input format (If using API mostly)
```
<|im_start|>system
You are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>
<|im_start|>user
{instructions}
{git_diff}<|im_end|>
<|im_start|>assistant
```
And the model will predict the rest of the content -> {assistant output}<|im_end|>