| --- |
| license: apache-2.0 |
| tags: |
| - summarization |
| - generated_from_trainer |
| datasets: |
| - multi_news |
| metrics: |
| - rouge |
| model-index: |
| - name: CS685-text-summarizer |
| results: |
| - task: |
| name: Sequence-to-sequence Language Modeling |
| type: text2text-generation |
| dataset: |
| name: multi_news |
| type: multi_news |
| config: default |
| split: train[:20%] |
| args: default |
| metrics: |
| - name: Rouge1 |
| type: rouge |
| value: 9.8777 |
| --- |
| |
| <!-- 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 |
|
|
| This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the multi_news dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.4960 |
| - Rouge1: 9.8777 |
| - Rouge2: 3.6509 |
| - Rougel: 7.597 |
| - Rougelsum: 9.0495 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | 2.8402 | 1.0 | 1349 | 2.5256 | 9.7548 | 3.5429 | 7.5078 | 8.9174 | |
| | 2.5581 | 2.0 | 2698 | 2.5011 | 9.7256 | 3.6262 | 7.5644 | 8.8904 | |
| | 2.3908 | 3.0 | 4047 | 2.4948 | 9.7569 | 3.5976 | 7.5209 | 8.8919 | |
| | 2.2744 | 4.0 | 5396 | 2.4875 | 9.9116 | 3.7758 | 7.6823 | 9.0881 | |
| | 2.1908 | 5.0 | 6745 | 2.4960 | 9.8777 | 3.6509 | 7.597 | 9.0495 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.29.1 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.12.0 |
| - Tokenizers 0.13.3 |
| |
