CS685-text-summarizer-2
This model is a fine-tuned version of facebook/bart-base on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.7516
- Rouge1: 17.4066
- Rouge2: 14.022
- Rougel: 16.9378
- Rougelsum: 17.0519
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: 6
- eval_batch_size: 6
- 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 |
|---|---|---|---|---|---|---|---|
| 2.3529 | 1.0 | 1052 | 1.9277 | 17.1288 | 13.5932 | 16.6346 | 16.7728 |
| 1.9686 | 2.0 | 2104 | 1.8297 | 17.2756 | 13.7685 | 16.7924 | 16.9242 |
| 1.789 | 3.0 | 3156 | 1.7903 | 17.4219 | 14.0205 | 16.9082 | 17.0564 |
| 1.6619 | 4.0 | 4208 | 1.7632 | 17.5055 | 14.1186 | 16.996 | 17.1265 |
| 1.5819 | 5.0 | 5260 | 1.7516 | 17.4066 | 14.022 | 16.9378 | 17.0519 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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Dataset used to train cs608/billsum-model-2
Evaluation results
- Rouge1 on billsumself-reported17.407