| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-t5/t5-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: TennesseeLegislationBillSummarizer |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # TennesseeLegislationBillSummarizer |
|
|
| 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: 0.9393 |
| - Rouge1: 0.5251 |
| - Rouge2: 0.4185 |
| - Rougel: 0.4987 |
| - Rougelsum: 0.4987 |
| - Gen Len: 19.6969 |
|
|
| ## 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: 4 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | 1.1485 | 1.0 | 15881 | 1.0192 | 0.5167 | 0.4071 | 0.4899 | 0.49 | 19.7533 | |
| | 1.0839 | 2.0 | 31762 | 0.9754 | 0.5185 | 0.4101 | 0.4918 | 0.4919 | 19.7608 | |
| | 1.0474 | 3.0 | 47643 | 0.9542 | 0.5228 | 0.4151 | 0.4961 | 0.4961 | 19.7375 | |
| | 1.0541 | 4.0 | 63524 | 0.9428 | 0.5247 | 0.4177 | 0.4981 | 0.4982 | 19.7032 | |
| | 1.0252 | 5.0 | 79405 | 0.9393 | 0.5251 | 0.4185 | 0.4987 | 0.4987 | 19.6969 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.1 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
| |
