| --- |
| license: apache-2.0 |
| base_model: google-t5/t5-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: senate_bills_summary_model |
| results: [] |
| datasets: |
| - MTSUFall2024SoftwareEngineering/UnitedStatesSenateBillsAndSummaries |
| 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. --> |
|
|
| # senate_bills_summary_model |
| |
| 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: 1.9099 |
| - Rouge1: 0.2477 |
| - Rouge2: 0.1963 |
| - Rougel: 0.2407 |
| - Rougelsum: 0.2406 |
| - Gen Len: 18.9992 |
| |
| ## Model description |
| |
| This model is a fine-tuned Google T5-Small model that is fine-tuned to summarize United States Senate Bills. |
| |
| ## Intended uses & limitations |
| |
| Summarize United States Federal Legislation. |
| |
| ## Training and evaluation data |
| |
| Trained on ~13.1k 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | 2.2318 | 1.0 | 749 | 1.9710 | 0.2475 | 0.1952 | 0.2405 | 0.2402 | 18.9985 | |
| | 2.1782 | 2.0 | 1498 | 1.9331 | 0.2478 | 0.1959 | 0.2408 | 0.2406 | 18.9992 | |
| | 2.1355 | 3.0 | 2247 | 1.9141 | 0.2479 | 0.1961 | 0.2409 | 0.2407 | 18.9992 | |
| | 2.1079 | 4.0 | 2996 | 1.9099 | 0.2477 | 0.1963 | 0.2407 | 0.2406 | 18.9992 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.1 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
