Add model card
Browse files
README.md
CHANGED
@@ -1,3 +1,58 @@
|
|
1 |
---
|
2 |
license: apache-2.0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
---
|
2 |
license: apache-2.0
|
3 |
+
language:
|
4 |
+
- code
|
5 |
+
- en
|
6 |
+
datasets:
|
7 |
+
- saridormi/commit-chronicle
|
8 |
+
pipeline_tag: text2text-generation
|
9 |
+
tags:
|
10 |
+
- code
|
11 |
+
- commit_message_generation
|
12 |
---
|
13 |
+
|
14 |
+
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.
|
15 |
+
|
16 |
+
## Details
|
17 |
+
|
18 |
+
> π For further details, please refer to:
|
19 |
+
> * **Paper**: TODO
|
20 |
+
> * **Repository**: [https://github.com/JetBrains-Research/commit_message_generation](https://github.com/JetBrains-Research/commit_message_generation)
|
21 |
+
|
22 |
+
|
23 |
+
* This model is based on [`Salesforce/codet5-base`](https://huggingface.co/Salesforce/codet5-base) checkpoint from π [CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation](https://aclanthology.org/2021.emnlp-main.685/).
|
24 |
+
* This model was trained with commit diffs, WITHOUT commit message history.
|
25 |
+
* This model was trained on the CommitChronicle dataset introduced in our study.
|
26 |
+
* Our hyperparameter setting is mostly based on π [RACE: Retrieval-augmented Commit Message Generation](https://aclanthology.org/2022.emnlp-main.372/).
|
27 |
+
The exact values are provided below:
|
28 |
+
|
29 |
+
| Hyperparameter | Value |
|
30 |
+
|:--------------------------:|:-------------------------------------------------------------------------------------------------------------------------------------------:|
|
31 |
+
| Encoder context max length | 512 |
|
32 |
+
| Decoder context max length | 512 |
|
33 |
+
| Number of training epochs | 1 |
|
34 |
+
| Batch size | 32 |
|
35 |
+
| Optimizer | [AdamW](https://pytorch.org/docs/1.12/generated/torch.optim.AdamW.html?highlight=adamw#torch.optim.AdamW) |
|
36 |
+
| Warmup | [Linear](https://huggingface.co/docs/transformers/v4.21.3/en/main_classes/optimizer_schedules#transformers.get_linear_schedule_with_warmup) |
|
37 |
+
| Number of warmup steps | 100 |
|
38 |
+
| Peak learning rate | 0.00002 |
|
39 |
+
|
40 |
+
|
41 |
+
## Available checkpoints
|
42 |
+
|
43 |
+
We also released checkpoints for other models fine-tuned as part of our study.
|
44 |
+
|
45 |
+
* Models trained *with commit message history*:
|
46 |
+
* **CodeT5:** π€ [`JetBrains-Research/cmg-codet5-with-history`](https://huggingface.co/JetBrains-Research/cmg-codet5-with-history)
|
47 |
+
* **CodeReviewer:** π€ [`JetBrains-Research/cmg-codereviewer-with-history`](https://huggingface.co/JetBrains-Research/cmg-codereviewer-with-history)
|
48 |
+
* **RACE:** π€ [`JetBrains-Research/cmg-race-with-history`](https://huggingface.co/JetBrains-Research/cmg-race-with-history)
|
49 |
+
* Models trained *without commit message history*:
|
50 |
+
* **CodeT5:** π€ [`JetBrains-Research/cmg-codet5-without-history`](https://huggingface.co/JetBrains-Research/cmg-codet5-without-history) (this model)
|
51 |
+
* **CodeReviewer:** π€ [`JetBrains-Research/cmg-codereviewer-without-history`](https://huggingface.co/JetBrains-Research/cmg-codereviewer-without-history)
|
52 |
+
* **RACE:** π€ [`JetBrains-Research/cmg-race-without-history`](https://huggingface.co/JetBrains-Research/cmg-race-without-history)
|
53 |
+
|
54 |
+
## Citation
|
55 |
+
|
56 |
+
```
|
57 |
+
TODO
|
58 |
+
```
|