bart-base-finetuned-multi-news
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.6353
- Rouge1: 15.1146
- Rouge2: 5.3873
- Rougel: 11.4132
- Rougelsum: 13.2739
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5.6e-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
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.9189 | 1.0 | 625 | 2.4645 | 15.2063 | 5.2852 | 11.5864 | 13.4208 |
| 2.4697 | 2.0 | 1250 | 2.4706 | 15.3737 | 5.4725 | 11.7465 | 13.5681 |
| 2.1831 | 3.0 | 1875 | 2.4789 | 14.8306 | 5.0857 | 11.2416 | 13.1072 |
| 1.9598 | 4.0 | 2500 | 2.5299 | 15.1744 | 5.5465 | 11.6445 | 13.4053 |
| 1.7777 | 5.0 | 3125 | 2.5799 | 14.9417 | 5.2124 | 11.3553 | 13.1401 |
| 1.6454 | 6.0 | 3750 | 2.6028 | 14.9804 | 5.333 | 11.294 | 13.2385 |
| 1.554 | 7.0 | 4375 | 2.6353 | 15.1146 | 5.3873 | 11.4132 | 13.2739 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3