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

# my_awesome_billsum_model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0467
- Rouge1: 0.7832
- Rouge2: 0.692
- Rougel: 0.781
- Rougelsum: 0.7805
- Gen Len: 11.6071

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 56   | 4.9294          | 0.0    | 0.0    | 0.0    | 0.0       | 16.558  |
| No log        | 2.0   | 112  | 2.2288          | 0.0    | 0.0    | 0.0    | 0.0       | 13.5357 |
| No log        | 3.0   | 168  | 0.4763          | 0.0045 | 0.0045 | 0.0045 | 0.0045    | 10.6518 |
| No log        | 4.0   | 224  | 0.1138          | 0.7232 | 0.6205 | 0.7245 | 0.7236    | 11.5893 |
| No log        | 5.0   | 280  | 0.0654          | 0.7417 | 0.6339 | 0.7417 | 0.7402    | 11.6607 |
| No log        | 6.0   | 336  | 0.0587          | 0.7321 | 0.6205 | 0.7321 | 0.7309    | 11.5938 |
| No log        | 7.0   | 392  | 0.0552          | 0.7496 | 0.6473 | 0.7491 | 0.7491    | 11.625  |
| No log        | 8.0   | 448  | 0.0533          | 0.7714 | 0.6786 | 0.7714 | 0.7709    | 11.6562 |
| 1.6431        | 9.0   | 504  | 0.0518          | 0.781  | 0.692  | 0.7832 | 0.7805    | 11.6161 |
| 1.6431        | 10.0  | 560  | 0.0505          | 0.764  | 0.6652 | 0.7632 | 0.7614    | 11.6607 |
| 1.6431        | 11.0  | 616  | 0.0494          | 0.7778 | 0.6875 | 0.78   | 0.7773    | 11.6116 |
| 1.6431        | 12.0  | 672  | 0.0488          | 0.7778 | 0.6875 | 0.78   | 0.7773    | 11.6116 |
| 1.6431        | 13.0  | 728  | 0.0483          | 0.781  | 0.692  | 0.7815 | 0.7805    | 11.6161 |
| 1.6431        | 14.0  | 784  | 0.0479          | 0.781  | 0.692  | 0.7815 | 0.7805    | 11.6071 |
| 1.6431        | 15.0  | 840  | 0.0475          | 0.7852 | 0.6964 | 0.7839 | 0.7842    | 11.6205 |
| 1.6431        | 16.0  | 896  | 0.0471          | 0.7812 | 0.692  | 0.781  | 0.7805    | 11.5982 |
| 1.6431        | 17.0  | 952  | 0.0469          | 0.7884 | 0.7009 | 0.7879 | 0.7869    | 11.625  |
| 0.062         | 18.0  | 1008 | 0.0468          | 0.7832 | 0.692  | 0.781  | 0.7805    | 11.6071 |
| 0.062         | 19.0  | 1064 | 0.0467          | 0.7864 | 0.6964 | 0.7839 | 0.7837    | 11.6027 |
| 0.062         | 20.0  | 1120 | 0.0467          | 0.7832 | 0.692  | 0.781  | 0.7805    | 11.6071 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0