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bart-base-finetuned-xsum
This model is a fine-tuned version of facebook/bart-base on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.1755
- Rouge1: 34.6293
- Rouge2: 13.4749
- Rougel: 28.2616
- Rougelsum: 28.2553
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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.4765 | 1.0 | 1000 | 2.0873 | 33.9596 | 12.722 | 27.4135 | 27.4062 |
| 1.9854 | 2.0 | 2000 | 2.0802 | 33.6802 | 12.8965 | 27.4061 | 27.4064 |
| 1.6677 | 3.0 | 3000 | 2.0998 | 34.2038 | 13.1362 | 27.8808 | 27.8806 |
| 1.4313 | 4.0 | 4000 | 2.1404 | 34.8491 | 13.4154 | 28.2768 | 28.2702 |
| 1.275 | 5.0 | 5000 | 2.1755 | 34.6293 | 13.4749 | 28.2616 | 28.2553 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
