readme: ---
  tags:
  - generated_from_trainer
  - seq2seq
  model-index:
  - name: codebert-gpt2-commitgen
    results: []
  language:
  - en
  metrics:
  - rouge
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # codebert-gpt2-commitgen
  
  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 
  Siyuan Jiang and Collin McMillan. 
  Heres are the links
  
  Paper :https://arxiv.org/abs/1708.09492
  Data : https://sjiang1.github.io/commitgen
  
  ## Model description
  
  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.
  
  
  ## Intended uses & limitations
  
  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. 
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 3
  
  ### Training results
  
  - global_step=4521
  - training_loss=3.55994465065804
  - train_runtime: 3300.0492
  - train_samples_per_second: 21.919
  - train_steps_per_second: 1.37
  - total_flos: 1.062667587499776e+16
  - train_loss: 3.55994465065804
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Tokenizers 0.13.2