| --- |
| license: apache-2.0 |
| tags: |
| - summarization |
| - generated_from_trainer |
| datasets: |
| - billsum |
| metrics: |
| - rouge |
| model-index: |
| - name: CS685-text-summarizer-2 |
| results: |
| - task: |
| name: Sequence-to-sequence Language Modeling |
| type: text2text-generation |
| dataset: |
| name: billsum |
| type: billsum |
| config: default |
| split: train[:20%] |
| args: default |
| metrics: |
| - name: Rouge1 |
| type: rouge |
| value: 17.1607 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # CS685-text-summarizer-2 |
|
|
| This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the billsum dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.7651 |
| - Rouge1: 17.1607 |
| - Rouge2: 13.943 |
| - Rougel: 16.6793 |
| - Rougelsum: 16.8422 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
| | 2.4547 | 1.0 | 569 | 1.9895 | 16.6343 | 13.0432 | 16.1262 | 16.2449 | |
| | 2.0246 | 2.0 | 1138 | 1.8688 | 16.939 | 13.4711 | 16.4359 | 16.5797 | |
| | 1.818 | 3.0 | 1707 | 1.8075 | 17.1388 | 13.827 | 16.6136 | 16.7574 | |
| | 1.6831 | 4.0 | 2276 | 1.7744 | 17.2292 | 13.9353 | 16.6961 | 16.8786 | |
| | 1.5956 | 5.0 | 2845 | 1.7651 | 17.1607 | 13.943 | 16.6793 | 16.8422 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.28.0 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.12.0 |
| - Tokenizers 0.13.3 |
|
|
