--- license: apache-2.0 language: - code - en datasets: - saridormi/commit-chronicle tags: - code - commit_message_generation pipeline_tag: text2text-generation --- # CMG/CMC: CodeT5 (without history) This is the checkpoint for [CodeT5](https://huggingface.co/Salesforce/codet5-base) 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**: TODO > * **Repository**: [https://github.com/JetBrains-Research/commit_message_generation](https://github.com/JetBrains-Research/commit_message_generation) * This model is based on [`Salesforce/codet5-base`](https://huggingface.co/Salesforce/codet5-base) checkpoint from 📜 [CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation](https://aclanthology.org/2021.emnlp-main.685/). * 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) (this model) * **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) ## Citation ``` TODO ```