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--- |
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tags: |
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- generated_from_trainer |
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- seq2seq |
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model-index: |
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- name: codebert-gpt2-commitgen |
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results: [] |
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language: |
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- en |
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metrics: |
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- rouge |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# codebert-gpt2-commitgen |
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This model is a fine-tuned version [](https://huggingface.co/) on dataset provided in the paper titled "Towards Automatic Generation of Short Summaries of Commits" by |
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Siyuan Jiang and Collin McMillan. |
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Heres are the links |
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Paper :https://arxiv.org/abs/1708.09492 |
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Data : https://sjiang1.github.io/commitgen |
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## Model description |
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This is a sequence2sequence model with microsoft/codebert-base as encoder and gpt2 as decoder. Givena gitdiff file, this model can generate a short commit message summarizing the change. |
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## Intended uses & limitations |
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The intended use is to automate github commit message. One limitation to consider is that the model can generate a summary of changes, but is only confined to type of change and might not be able to provide details about the change or output specific keywords related to change. |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 2000 |
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- num_epochs: 3 |
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### Training results |
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- global_step=4521 |
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- training_loss=3.55994465065804 |
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- train_runtime: 3300.0492 |
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- train_samples_per_second: 21.919 |
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- train_steps_per_second: 1.37 |
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- total_flos: 1.062667587499776e+16 |
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- train_loss: 3.55994465065804 |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Tokenizers 0.13.2 |
