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---
language:
- code
- en
license: apache-2.0
tags:
- commit_message_generation
- code
datasets:
- JetBrains-Research/commit-chronicle
pipeline_tag: text2text-generation
---
# CMG/CMC: RACE (without history)
This is the checkpoint for [RACE](https://aclanthology.org/2022.emnlp-main.372.pdf) model, fine-tuned for the commit message generation (and/or completion) task as part of the paper "From Commit Message Generation to History-Aware Commit Message Completion", ASE 2023.
## Details
> 🔍 For further details, please refer to:
> * **Paper**: [https://arxiv.org/abs/2308.07655](https://arxiv.org/abs/2308.07655)
> * **Repository**: [https://github.com/JetBrains-Research/commit_message_generation](https://github.com/JetBrains-Research/commit_message_generation)
* This model is based on the fine-tuned CodeT5 checkpoint [`JetBrains-Research/cmg-codet5-without-history`](https://huggingface.co/JetBrains-Research/cmg-codet5-without-history) and uses RACE architecture introduced in 📜 [RACE: Retrieval-Augmented Commit Message Generation](https://aclanthology.org/2022.emnlp-main.372.pdf).
* Note: Requires a custom model class. Check [our implementation](https://github.com/JetBrains-Research/commit_message_generation/blob/appendix_cmg/src/model/configurations/utils/race.py) or [the replication package](https://github.com/DeepSoftwareAnalytics/RACE) provided by RACE authors.
* This model was trained with commit diffs, WITHOUT commit message history.
* This model was trained on the CommitChronicle dataset introduced in our study.
* Our hyperparameter setting is mostly based on 📜 [RACE: Retrieval-augmented Commit Message Generation](https://aclanthology.org/2022.emnlp-main.372/).
The exact values are provided below:
| Hyperparameter | Value |
|:--------------------------:|:-------------------------------------------------------------------------------------------------------------------------------------------:|
| Encoder context max length | 512 |
| Decoder context max length | 512 |
| Number of training epochs | 1 |
| Batch size | 32 |
| Optimizer | [AdamW](https://pytorch.org/docs/1.12/generated/torch.optim.AdamW.html?highlight=adamw#torch.optim.AdamW) |
| Warmup | [Linear](https://huggingface.co/docs/transformers/v4.21.3/en/main_classes/optimizer_schedules#transformers.get_linear_schedule_with_warmup) |
| Number of warmup steps | 100 |
| Peak learning rate | 0.00002 |
## Available checkpoints
We also released checkpoints for other models fine-tuned as part of our study.
* Models trained *with commit message history*:
* **CodeT5:** 🤗 [`JetBrains-Research/cmg-codet5-with-history`](https://huggingface.co/JetBrains-Research/cmg-codet5-with-history)
* **CodeReviewer:** 🤗 [`JetBrains-Research/cmg-codereviewer-with-history`](https://huggingface.co/JetBrains-Research/cmg-codereviewer-with-history)
* **RACE:** 🤗 [`JetBrains-Research/cmg-race-with-history`](https://huggingface.co/JetBrains-Research/cmg-race-with-history)
* Models trained *without commit message history*:
* **CodeT5:** 🤗 [`JetBrains-Research/cmg-codet5-without-history`](https://huggingface.co/JetBrains-Research/cmg-codet5-without-history)
* **CodeReviewer:** 🤗 [`JetBrains-Research/cmg-codereviewer-without-history`](https://huggingface.co/JetBrains-Research/cmg-codereviewer-without-history)
* **RACE:** 🤗 [`JetBrains-Research/cmg-race-without-history`](https://huggingface.co/JetBrains-Research/cmg-race-without-history) (this model)
## Citation
```
TODO
``` |