This model is a fine-tuned version of facebook/bart-large-cnn on the SGH news articles and summaries dataset. It achieves the following results on the evaluation set:

• Loss: 2.7389
• Rouge1: 0.5297
• Rouge2: 0.3602
• Rougel: 0.3961
• Rougelsum: 0.4821
• Gen Len: 137.9091

Model description

This model was created to generate summaries of news articles.

Intended uses & limitations

The model takes up to maximum article length of 1024 tokens and generates a summary of maximum length of 512 tokens.

Training data

This model was trained on 100+ articles and summaries from SGH.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 10
• label_smoothing_factor: 0.1

Framework versions

• Transformers 4.23.1
• Pytorch 1.12.1+cu113
• Datasets 2.6.1
• Tokenizers 0.13.1