---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: FL_Legislature_Summarizer
  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. -->

# FL_Legislature_Summarizer

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: 0.3128
- Rouge1: 0.6498
- Rouge2: 0.6141
- Rougel: 0.6438
- Rougelsum: 0.644
- Gen Len: 19.5408

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.4196        | 1.0   | 2095 | 0.3458          | 0.6444 | 0.6051 | 0.6381 | 0.6382    | 19.5489 |
| 0.2907        | 2.0   | 4190 | 0.3141          | 0.6498 | 0.6124 | 0.6437 | 0.644     | 19.5403 |
| 0.2901        | 3.0   | 6285 | 0.3128          | 0.6498 | 0.6141 | 0.6438 | 0.644     | 19.5408 |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1