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pegasus_summarization_pretrained
This model is a fine-tuned version of google/pegasus-xsum on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.9463
- Rouge1: 0.3979
- Rouge2: 0.1963
- Rougel: 0.2889
- Rougelsum: 0.2887
- Gen Len: 61.9919
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 124 | 2.0226 | 0.3896 | 0.1882 | 0.2838 | 0.2839 | 61.5444 |
| No log | 2.0 | 248 | 1.9736 | 0.3991 | 0.1963 | 0.291 | 0.2907 | 61.9194 |
| No log | 3.0 | 372 | 1.9542 | 0.3977 | 0.196 | 0.2889 | 0.2885 | 61.9718 |
| No log | 4.0 | 496 | 1.9463 | 0.3979 | 0.1963 | 0.2889 | 0.2887 | 61.9919 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
