DunnBC22's picture
Update README.md
ccdabbf
metadata
tags:
  - generated_from_trainer
model-index:
  - name: pegasus-multi_news-NewsSummarization_BBC
    results: []
language:
  - en
metrics:
  - rouge
pipeline_tag: summarization

pegasus-multi_news-NewsSummarization_BBC

This model is a fine-tuned version of google/pegasus-multi_news.

Model description

This is a text summarization model of news articles.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Text%20Summarization/Text_Summarization_BBC_News-Pegasus.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: https://www.kaggle.com/datasets/pariza/bbc-news-summary

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 2

Training results

Unfortunately, I did not set the metrics to automatically upload here. They are as follows:

Training Loss Epoch Step rouge1 rouge2 rougeL rougeLsum
6.41979 2.0 214 0.584474 0.463574 0.408729 0.408431

Framework versions

  • Transformers 4.21.3
  • Pytorch 1.12.1
  • Datasets 2.4.0
  • Tokenizers 0.12.1