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---
tags:
- generated_from_trainer
model-index:
- name: pegasus-multi_news-NewsSummarization_BBC
results: []
---
# pegasus-multi_news-NewsSummarization_BBC
This model is a fine-tuned version of [google/pegasus-multi_news](https://huggingface.co/google/pegasus-multi_news) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
I used this to improve my skillset. I thank all of authors of the different technologies and
dataset(s) for their contributions that have this possible. I am not too worried about getting
credit for my part, but make sure to properly cite the authors of the different technologies
and dataset(s) as they absolutely deserve credit for their contributions.
## Training and evaluation data
Dataset Source: https://www.kaggle.com/datasets/pariza/bbc-news-summary
## Training procedure
Here is the link to the script that I created to train this project:
https://github.com/DunnBC22/NLP_Projects/blob/main/Text%20Summarization/Text_Summarization_BBC_News-Pegasus.ipynb
### 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 |