---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
- NLP
- text-to-text
- Summarization
metrics:
- rouge
model-index:
- name: MTSUFall2024SoftwareEngineering
  results: []
datasets:
- MTSUFall2024SoftwareEngineering/UnitedStatesSenateBillsAndSummaries
language:
- en
---

<!-- 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. -->

# 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: 1.9830
- Rouge1: 0.2539
- Rouge2: 0.201
- Rougel: 0.2469
- Rougelsum: 0.2469
- Gen Len: 18.9996

## Model description

More information needed

## Intended uses & limitations

Used for Middle Tennessee State University's Software Engineering Fall 2024 class.

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.7481        | 1.0   | 749  | 2.1062          | 0.2552 | 0.1993 | 0.2475 | 0.2475    | 18.9996 |
| 2.3354        | 2.0   | 1498 | 2.0224          | 0.2531 | 0.2    | 0.246  | 0.246     | 18.9996 |
| 2.2351        | 3.0   | 2247 | 1.9929          | 0.2542 | 0.2011 | 0.2471 | 0.247     | 18.9996 |
| 2.193         | 4.0   | 2996 | 1.9830          | 0.2539 | 0.201  | 0.2469 | 0.2469    | 18.9996 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1