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---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: senate_bills_summary_model
  results: []
datasets:
- cheaptrix/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. -->

# senate_bills_summary_model

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: 1.9099
- Rouge1: 0.2477
- Rouge2: 0.1963
- Rougel: 0.2407
- Rougelsum: 0.2406
- Gen Len: 18.9992

## Model description

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

## Intended uses & limitations

Summarize United States Federal Legislation.

## Training and evaluation data

Trained on ~13.1k 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.2318        | 1.0   | 749  | 1.9710          | 0.2475 | 0.1952 | 0.2405 | 0.2402    | 18.9985 |
| 2.1782        | 2.0   | 1498 | 1.9331          | 0.2478 | 0.1959 | 0.2408 | 0.2406    | 18.9992 |
| 2.1355        | 3.0   | 2247 | 1.9141          | 0.2479 | 0.1961 | 0.2409 | 0.2407    | 18.9992 |
| 2.1079        | 4.0   | 2996 | 1.9099          | 0.2477 | 0.1963 | 0.2407 | 0.2406    | 18.9992 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1