---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
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-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5203
- Rouge1: 0.1478
- Rouge2: 0.0536
- Rougel: 0.1237
- Rougelsum: 0.1236
- Gen Len: 20.0

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 62   | 2.8114          | 0.132  | 0.0395 | 0.1117 | 0.1115    | 20.0    |
| No log        | 2.0   | 124  | 2.5983          | 0.1384 | 0.0478 | 0.1169 | 0.1169    | 20.0    |
| No log        | 3.0   | 186  | 2.5372          | 0.1468 | 0.0545 | 0.1236 | 0.1235    | 20.0    |
| No log        | 4.0   | 248  | 2.5203          | 0.1478 | 0.0536 | 0.1237 | 0.1236    | 20.0    |


### Framework versions

- Transformers 5.0.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1