---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-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-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: 1.9564
- Rouge1: 50.3551
- Rouge2: 29.3717
- Rougel: 39.4102
- Rougelsum: 43.6247

## 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.5468        | 1.0   | 1185 | 2.0937          | 48.625  | 27.492  | 37.671  | 41.4628   |
| 2.2867        | 2.0   | 2370 | 2.0155          | 49.2547 | 28.248  | 38.39   | 42.3374   |
| 2.2241        | 3.0   | 3555 | 1.9796          | 49.8802 | 28.8333 | 38.8829 | 43.027    |
| 2.1925        | 4.0   | 4740 | 1.9620          | 50.07   | 28.9961 | 39.1086 | 43.3251   |
| 2.1791        | 5.0   | 5925 | 1.9576          | 50.2626 | 29.1819 | 39.2415 | 43.4781   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1