Codet5 Base Generate Docstrings For Python Condensed

🚀 codet5-base-Generate_Docstrings_for_Python-Condensed

This model is a fine - tuned version of Salesforce/codet5-base, which can generate docstrings for Python functions. It offers high - quality results in docstring prediction, as demonstrated by its performance on the evaluation set.

🚀 Quick Start

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

• Loss: 0.6199
• Rouge1: 0.5017
• Rouge2: 0.374
• Rougel: 0.4866
• Rougelsum: 0.4864
• Gen Len: 13.8909

✨ Features

• Docstring Prediction: This model predicts the docstring (the output) for a function (the input).
• High Performance: It achieves good results on evaluation metrics such as Rouge scores.

📚 Documentation

Model description

This model predicts the docstring (the output) for a function (the input).

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Generate%20Docstrings/Smol%20Dataset/Code_T5_Project-Base%20Checkpoint.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: calum/the-stack-smol-python-docstrings (from HuggingFace Datasets; https://huggingface.co/datasets/calum/the-stack-smol-python-docstrings)

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: 2

Training results

Framework versions

• Transformers 4.27.4
• Pytorch 2.0.0
• Datasets 2.11.0
• Tokenizers 0.13.3

📄 License

This model is licensed under the Apache - 2.0 license.