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

# t5-small-finetuned-billsum

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3166
- Rouge1: 58.6163
- Rouge2: 41.6107
- Rougel: 51.5177
- Rougelsum: 52.8486
- Gen Len: 62.2894

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.5373        | 0.4219 | 500  | 1.7306          | 44.8884 | 29.9047 | 38.8732 | 39.7098   | 49.8626 |
| 1.8175        | 0.8439 | 1000 | 1.5164          | 53.4663 | 36.8936 | 46.4756 | 47.6133   | 57.6953 |
| 1.6775        | 1.2658 | 1500 | 1.4401          | 55.9549 | 38.7969 | 48.6918 | 49.9216   | 60.5867 |
| 1.6           | 1.6878 | 2000 | 1.4016          | 56.8423 | 39.5972 | 49.5877 | 50.8088   | 61.5580 |
| 1.5717        | 2.1097 | 2500 | 1.3736          | 57.4282 | 40.2126 | 50.1498 | 51.3818   | 61.9033 |
| 1.5389        | 2.5316 | 3000 | 1.3570          | 57.6909 | 40.5046 | 50.4987 | 51.7769   | 62.0116 |
| 1.5183        | 2.9536 | 3500 | 1.3426          | 58.2372 | 41.1473 | 51.0517 | 52.3423   | 62.1297 |
| 1.499         | 3.3755 | 4000 | 1.3310          | 58.326  | 41.2564 | 51.1817 | 52.4513   | 62.2423 |
| 1.4845        | 3.7975 | 4500 | 1.3232          | 58.4925 | 41.5426 | 51.3865 | 52.6942   | 62.2276 |
| 1.4888        | 4.2194 | 5000 | 1.3203          | 58.5475 | 41.5865 | 51.4574 | 52.791    | 62.2710 |
| 1.48          | 4.6414 | 5500 | 1.3166          | 58.6163 | 41.6107 | 51.5177 | 52.8486   | 62.2894 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1