| --- |
| license: apache-2.0 |
| base_model: t5-base |
| tags: |
| - generated_from_trainer |
| datasets: |
| - billsum |
| metrics: |
| - rouge |
| model-index: |
| - name: my_awesome_billsum_model |
| 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: 0.2033 |
| --- |
| |
| <!-- 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. --> |
|
|
| # my_awesome_billsum_model |
| |
| This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the billsum dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.6638 |
| - Rouge1: 0.2033 |
| - Rouge2: 0.1149 |
| - Rougel: 0.1762 |
| - Rougelsum: 0.1759 |
| - 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: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | No log | 1.0 | 248 | 1.9584 | 0.1999 | 0.1073 | 0.1716 | 0.1717 | 19.0 | |
| | No log | 2.0 | 496 | 1.8621 | 0.195 | 0.1045 | 0.1685 | 0.1682 | 19.0 | |
| | 2.2512 | 3.0 | 744 | 1.8095 | 0.1973 | 0.1109 | 0.1728 | 0.1727 | 19.0 | |
| | 2.2512 | 4.0 | 992 | 1.7797 | 0.1989 | 0.1102 | 0.1724 | 0.1724 | 19.0 | |
| | 1.8144 | 5.0 | 1240 | 1.7505 | 0.1997 | 0.112 | 0.1735 | 0.1736 | 19.0 | |
| | 1.8144 | 6.0 | 1488 | 1.7308 | 0.2003 | 0.1134 | 0.1746 | 0.1744 | 19.0 | |
| | 1.6898 | 7.0 | 1736 | 1.7145 | 0.199 | 0.1114 | 0.1732 | 0.173 | 19.0 | |
| | 1.6898 | 8.0 | 1984 | 1.7083 | 0.1977 | 0.1106 | 0.1718 | 0.1716 | 19.0 | |
| | 1.5997 | 9.0 | 2232 | 1.6983 | 0.2014 | 0.1127 | 0.175 | 0.175 | 19.0 | |
| | 1.5997 | 10.0 | 2480 | 1.6923 | 0.2014 | 0.1153 | 0.1754 | 0.1753 | 19.0 | |
| | 1.5403 | 11.0 | 2728 | 1.6826 | 0.2009 | 0.1134 | 0.1752 | 0.1751 | 19.0 | |
| | 1.5403 | 12.0 | 2976 | 1.6768 | 0.2003 | 0.1125 | 0.1745 | 0.1744 | 19.0 | |
| | 1.491 | 13.0 | 3224 | 1.6722 | 0.2016 | 0.1146 | 0.1756 | 0.1755 | 19.0 | |
| | 1.491 | 14.0 | 3472 | 1.6750 | 0.2039 | 0.1164 | 0.1773 | 0.177 | 19.0 | |
| | 1.4496 | 15.0 | 3720 | 1.6679 | 0.2023 | 0.1147 | 0.1765 | 0.1763 | 19.0 | |
| | 1.4496 | 16.0 | 3968 | 1.6677 | 0.2032 | 0.1148 | 0.177 | 0.1768 | 19.0 | |
| | 1.4241 | 17.0 | 4216 | 1.6640 | 0.2021 | 0.1135 | 0.1752 | 0.175 | 19.0 | |
| | 1.4241 | 18.0 | 4464 | 1.6645 | 0.2027 | 0.1155 | 0.1766 | 0.1764 | 19.0 | |
| | 1.4025 | 19.0 | 4712 | 1.6632 | 0.2028 | 0.1149 | 0.1761 | 0.1757 | 19.0 | |
| | 1.4025 | 20.0 | 4960 | 1.6638 | 0.2033 | 0.1149 | 0.1762 | 0.1759 | 19.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.31.0 |
| - Pytorch 2.0.1 |
| - Datasets 2.14.1 |
| - Tokenizers 0.13.3 |
| |
