---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: billsum-model
  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. -->

# billsum-model

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2894
- Rouge1: 0.4161
- Rouge2: 0.1838
- Rougel: 0.2786
- Rougelsum: 0.2791
- Gen Len: 149.0

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| No log        | 1.0   | 248  | 2.4737          | 0.3984 | 0.1645 | 0.261  | 0.2607    | 144.9718 |
| No log        | 2.0   | 496  | 2.3435          | 0.4126 | 0.1783 | 0.2762 | 0.2764    | 148.754  |
| 3.4184        | 3.0   | 744  | 2.3004          | 0.4162 | 0.1814 | 0.2765 | 0.2767    | 149.0    |
| 3.4184        | 4.0   | 992  | 2.2894          | 0.4161 | 0.1838 | 0.2786 | 0.2791    | 149.0    |


### Framework versions

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