---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: billsum-model-z
  results: []
datasets:
- FiscalNote/billsum
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. -->

# billsum-model-z

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an [FiscalNote/billsum](https://huggingface.co/datasets/FiscalNote/billsum) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9649
- Rouge1: 0.473
- Rouge2: 0.2725
- Rougel: 0.3613
- Rougelsum: 0.3612
- Gen Len: 129.5922

## 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: 1e-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
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 2.2403        | 1.0   | 4738 | 2.0142          | 0.470  | 0.2680 | 0.3586 | 0.3585    | 130.1138 |
| 2.1743        | 2.0   | 9476 | 1.9649          | 0.473  | 0.2725 | 0.3613 | 0.3612    | 129.5922 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3