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