Bart Fine Tuning Text Summarizer

This model is a fine-tuned version of facebook/bart-large-xsum on the BBC News Summary dataset.

If you'd like to use this model in a pipeline, you can load it easily with Hugging Face's transformers library:

from transformers import pipeline
summarizer = pipeline("summarization", model="Seif-Yasser/bart-large-xsum-finetuned-xsum")

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
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	84	0.8199	42.0809	35.1683	34.0117	35.9952	59.7371

Framework versions

• Transformers 4.44.0
• Pytorch 2.4.0
• Datasets 2.21.0
• Tokenizers 0.19.1