| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - billsum |
| metrics: |
| - rouge |
| model-index: |
| - name: t5summarization |
| results: |
| - task: |
| name: Sequence-to-sequence Language Modeling |
| type: text2text-generation |
| dataset: |
| name: billsum |
| type: billsum |
| config: default |
| split: ca_test |
| args: default |
| metrics: |
| - name: Rouge1 |
| type: rouge |
| value: 0.1862 |
| --- |
| |
| <!-- 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. --> |
|
|
| # t5summarization |
|
|
| This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.4353 |
| - Rouge1: 0.1862 |
| - Rouge2: 0.0831 |
| - Rougel: 0.1565 |
| - Rougelsum: 0.1562 |
| - Gen Len: 19.0 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | No log | 1.0 | 62 | 2.5150 | 0.1469 | 0.0544 | 0.1214 | 0.1216 | 19.0 | |
| | No log | 2.0 | 124 | 2.4668 | 0.1659 | 0.0671 | 0.1369 | 0.1369 | 19.0 | |
| | No log | 3.0 | 186 | 2.4418 | 0.1801 | 0.0793 | 0.1515 | 0.1513 | 19.0 | |
| | No log | 4.0 | 248 | 2.4353 | 0.1862 | 0.0831 | 0.1565 | 0.1562 | 19.0 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.28.1 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.12.0 |
| - Tokenizers 0.13.3 |
|
|
