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codet5-small-Generate_Docstrings_for_Python

This model is a fine-tuned version of Salesforce/codet5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.4116
  • Rouge1: 0.3381
  • Rouge2: 0.1541
  • Rougel: 0.3045
  • Rougelsum: 0.3214
  • Gen Len: 15.8088

Model description

This model is trained to provide the docstring for functions.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Generate%20Docstrings/Code_T5_Project.ipynb

Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

Training and evaluation data

Dataset Source: kejian/codesearchnet-python-raw (from HuggingFace Datasets; https://huggingface.co/datasets/kejian/codesearchnet-python-raw)

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-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
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.7447 1.0 7913 2.4116 0.3381 0.1541 0.3045 0.3214 15.8088

Framework versions

  • Transformers 4.27.3
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2
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Dataset used to train DunnBC22/codet5-small-Generate_Docstrings_for_Python

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