---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model_36
  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_36

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: 0.4601
- Rouge1: 0.9721
- Rouge2: 0.8819
- Rougel: 0.9256
- Rougelsum: 0.9271
- Gen Len: 4.9167

## 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   | 1.9874          | 0.4145 | 0.2913 | 0.3883 | 0.3891    | 17.6042 |
| No log        | 2.0   | 24   | 1.4300          | 0.4322 | 0.3091 | 0.4061 | 0.4068    | 17.0833 |
| No log        | 3.0   | 36   | 0.9451          | 0.5076 | 0.3886 | 0.4814 | 0.48      | 14.75   |
| No log        | 4.0   | 48   | 0.6345          | 0.8401 | 0.7297 | 0.7858 | 0.7884    | 7.625   |
| No log        | 5.0   | 60   | 0.5226          | 0.9591 | 0.8586 | 0.8998 | 0.9042    | 5.125   |
| No log        | 6.0   | 72   | 0.4907          | 0.9701 | 0.8736 | 0.9129 | 0.9167    | 4.8958  |
| No log        | 7.0   | 84   | 0.4783          | 0.9701 | 0.8736 | 0.9129 | 0.9167    | 4.8958  |
| No log        | 8.0   | 96   | 0.4697          | 0.9721 | 0.8819 | 0.9256 | 0.9271    | 4.9167  |
| No log        | 9.0   | 108  | 0.4627          | 0.9721 | 0.8819 | 0.9256 | 0.9271    | 4.9167  |
| No log        | 10.0  | 120  | 0.4601          | 0.9721 | 0.8819 | 0.9256 | 0.9271    | 4.9167  |


### Framework versions

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