| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-t5/t5-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: Final_Tuning |
| results: [] |
| --- |
| |
|
|
| # Final_Tuning |
| |
| This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on our [Congressional bill and summarization dataset](https://huggingface.co/datasets/cheaptrix/billsum-US_congress_and_house). |
| |
| It achieves the following results on the evaluation set: |
| - Loss: 1.4253 |
| - Rouge1: 0.2818 |
| - Rouge2: 0.2299 |
| - Rougel: 0.2729 |
| - Rougelsum: 0.2729 |
| - Gen Len: 18.9624 |
| |
| ## Model description |
| |
| MTSU SoftwareEngineering 2024: Fine-Tuned model for whatsinthebill.ai, a server hosted federal bill summarization model. |
| |
| Hyperparameters found using Optuna grid search. |
| |
| ## Intended uses & limitations |
| |
| To be used on congressional bills, acts, amendments, etc. as a summarization pipeline. |
| |
| ## Training and evaluation data |
| |
| Trained on the dataset of Congressional bills and summaries my team and I cleaned and collated. |
| |
| Can be found at https://huggingface.co/datasets/cheaptrix/billsum-US_congress_and_house |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 3.28e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | 1.7639 | 1.0 | 12429 | 1.5726 | 0.2754 | 0.2199 | 0.266 | 0.266 | 18.9728 | |
| | 1.658 | 2.0 | 24858 | 1.4926 | 0.2783 | 0.2246 | 0.2691 | 0.269 | 18.9693 | |
| | 1.6068 | 3.0 | 37287 | 1.4537 | 0.2819 | 0.2292 | 0.2728 | 0.2728 | 18.9616 | |
| | 1.5955 | 4.0 | 49716 | 1.4304 | 0.2812 | 0.2293 | 0.2723 | 0.2723 | 18.9615 | |
| | 1.5633 | 5.0 | 62145 | 1.4253 | 0.2818 | 0.2299 | 0.2729 | 0.2729 | 18.9624 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.2 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
