metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: codet5-small-Generate_Docstrings_for_Python
results: []
datasets:
- kejian/codesearchnet-python-raw
language:
- en
pipeline_tag: text2text-generation
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