---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: MTSUFall2024SoftwareEngineering
  results: []
datasets:
- cheaptrix/UnitedStatesSentateAndHouseBillsAndSummaries
language:
- en
---

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# MTSUFall2024SoftwareEngineering

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: 1.7579
- Rouge1: 0.268
- Rouge2: 0.2083
- Rougel: 0.258
- Rougelsum: 0.2582
- Gen Len: 18.9805

## Model description

This model is a fine-tuned Google T5-Small model that is fine-tuned to summarize United States Senate and House Bills.

## Intended uses & limitations

Summarize United States Federal Legislation.

## Training and evaluation data

Trained on ~51.9k bills and summaries.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 14
- eval_batch_size: 14
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.1182        | 1.0   | 3708  | 1.8807          | 0.2643 | 0.2029 | 0.2533 | 0.2534    | 18.9817 |
| 1.999         | 2.0   | 7416  | 1.8013          | 0.2663 | 0.2053 | 0.2558 | 0.2559    | 18.9833 |
| 1.9739        | 3.0   | 11124 | 1.7681          | 0.267  | 0.2066 | 0.2568 | 0.2569    | 18.9816 |
| 1.9448        | 4.0   | 14832 | 1.7579          | 0.268  | 0.2083 | 0.258  | 0.2582    | 18.9805 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1