t5-base-finance-news-summarization
This model is a fine-tuned version of t5-base for the purpose of summarizing finance-related news articles.
Model description
T5-Base Finance News Summarization is optimized for transforming lengthy financial news into concise summaries. This tool aids stakeholders in quickly understanding market dynamics and financial updates without reading full articles.
Intended uses & limitations
The model is intended for use in financial sectors by analysts, economists, and journalists needing quick summaries of finance news. It may not perform well with general news or in highly technical or academic finance contexts.
Training and evaluation data
Trained on a diverse collection of finance news articles from various reputable financial news sources, annotated with summaries to provide a comprehensive learning base.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Tokenizers 0.15.2
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