---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model_32
  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. -->

# my_awesome_billsum_model_32

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: 0.6953
- Rouge1: 0.9328
- Rouge2: 0.7819
- Rougel: 0.8546
- Rougelsum: 0.857
- Gen Len: 5.2083

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 12   | 2.1371          | 0.3875 | 0.2627 | 0.3679 | 0.3672    | 17.5625 |
| No log        | 2.0   | 24   | 1.6293          | 0.4137 | 0.286  | 0.3928 | 0.3924    | 16.5625 |
| No log        | 3.0   | 36   | 1.1556          | 0.478  | 0.347  | 0.4538 | 0.4505    | 14.6458 |
| No log        | 4.0   | 48   | 0.8702          | 0.7792 | 0.6558 | 0.7344 | 0.7311    | 8.2708  |
| No log        | 5.0   | 60   | 0.7539          | 0.9328 | 0.7819 | 0.8546 | 0.857     | 5.2083  |
| No log        | 6.0   | 72   | 0.7230          | 0.9328 | 0.7819 | 0.8546 | 0.857     | 5.2083  |
| No log        | 7.0   | 84   | 0.7094          | 0.9328 | 0.7819 | 0.8546 | 0.857     | 5.2083  |
| No log        | 8.0   | 96   | 0.7026          | 0.9328 | 0.7819 | 0.8546 | 0.857     | 5.2083  |
| No log        | 9.0   | 108  | 0.6978          | 0.9328 | 0.7819 | 0.8546 | 0.857     | 5.2083  |
| No log        | 10.0  | 120  | 0.6953          | 0.9328 | 0.7819 | 0.8546 | 0.857     | 5.2083  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1