| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-t5/t5-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: MTSUFall2024SoftwareEngineering |
| results: [] |
| datasets: |
| - cheaptrix/UnitedStatesSentateAndHouseBillsAndSummaries |
| language: |
| - en |
| --- |
| |
| <!-- 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. --> |
|
|
| # MTSUFall2024SoftwareEngineering |
|
|
| This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.7579 |
| - Rouge1: 0.268 |
| - Rouge2: 0.2083 |
| - Rougel: 0.258 |
| - Rougelsum: 0.2582 |
| - Gen Len: 18.9805 |
|
|
| ## Model description |
|
|
| This model is a fine-tuned Google T5-Small model that is fine-tuned to summarize United States Senate and House Bills. |
|
|
| ## Intended uses & limitations |
|
|
| Summarize United States Federal Legislation. |
|
|
| ## Training and evaluation data |
|
|
| Trained on ~51.9k bills and summaries. |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 14 |
| - eval_batch_size: 14 |
| - 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | 2.1182 | 1.0 | 3708 | 1.8807 | 0.2643 | 0.2029 | 0.2533 | 0.2534 | 18.9817 | |
| | 1.999 | 2.0 | 7416 | 1.8013 | 0.2663 | 0.2053 | 0.2558 | 0.2559 | 18.9833 | |
| | 1.9739 | 3.0 | 11124 | 1.7681 | 0.267 | 0.2066 | 0.2568 | 0.2569 | 18.9816 | |
| | 1.9448 | 4.0 | 14832 | 1.7579 | 0.268 | 0.2083 | 0.258 | 0.2582 | 18.9805 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.19.1 |
