YAML Metadata Warning: The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

CMG/CMC: CodeReviewer (without history)

This is the checkpoint for CodeReviewer 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

Repository: https://github.com/JetBrains-Research/commit_message_generation

This model is based on microsoft/codereviewer checkpoint from 📜 Automating Code Review Activities by Large-Scale Pre-training.
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. 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
Warmup	Linear
Number of warmup steps	100
Peak learning rate	0.00002